Rieger CG, Mcjunkin TR, Manic M, Amarasinghe K, 2021. Systems And Methods For Control System Security, US Patent.No. 10,896,261, Publication date January 19, 2021

VCU sold invention to industry entity for commercialization, Nov. 2021: Rieger CG, Mcjunkin TR, Manic M, Amarasinghe K, “ICS Resilient Security Technology (IReST)”, Docket No: MAN-19-110

Halepovic E,  Mustafa I, Nadeem T, 2021. Video Streaming at Mobile Edge. Issued as Patent No. 11,128,682 B2 by the United States Patent and Trademark Office, September 21, 2021

Bhatia S, Bhatia S, Ahmed I, 2021. Automated Waterloo Rubric for Concept Map Grading. IEEE Access,  doi:10.1109/ACCESS.2021.3124672 IF: 3.37

Dahir M, Qasim S, Ahmed I, 2021. Cronus: An Automated Feedback Tool for Concept Maps. IEEE Access, doi: 10.1109/ACCESS.2021.3106509 IF: 3.37

Rais M, Li Y, Ahmed I, 2021. Dynamic-thermal and localized filament-kinetic attacks on fused filament fabrication based 3D printing process. Additive Manufacturing, https://doi.org/10.1016/j.addma.2021.102200 IF: 11.00 (Q1 rank)

Rais M, Awad R, Lopez J, Ahmed I, 2021. JTAG-based PLC memory acquisition framework for industrial control systems. Forensic Science International: Digital Investigation, https://doi.org/10.1016/j.fsidi.2021.301196

Saeedi S, Panahi A, Arodz T, 2021. Quantum semi-supervised kernel learning. Quantum Machine Intelligence 3:24 https://doi.org/10.1007/s42484-021-00053-x

Hernandez SM, Bulut E, 2021. WiFederated: Scalable WiFi Sensing using Edge Based Federated Learning. IEEE Internet of Things Journal, https://doi.org/10.1109/JIOT.2021.3137793 IF: 9.471 (Q1 rank)

Yucel F, Bulut E, 2021. Online Stable Task Assignment in Opportunistic Mobile Crowdsensing with Uncertain Trajectories. IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3118134 https://ieeexplore.ieee.org/document/9560153 IF: 9.47 (Q1 rank)

Yucel F, Yuksel M, Bulut E, 2021. Coverage-Aware Stable Task Assignment in Opportunistic Mobile Crowdsensing. IEEE Transactions on Vehicular Technology (TVT), 70(4):3831-45. https://ieeexplore.ieee.org/document/9376990 IF: 5.98 (Q1 rank)

Erdin E, Cebe M, Akkaya K, Bulut E, Uluagac S, 2021. A scalable private Bitcoin payment channel network with privacy guarantees. Journal of Network and Computer Applications. 180:103021,doi:10.1016/j.jnca.2021.103021 . https://www.sciencedirect.com/science/article/abs/pii/S1084804521000485 IF: 6.28 (Q1 rank)

Roseberry M, Krawczyk B, Djenouri Y, Cano A, 2021. Self-Adjusting k Nearest Neighbors for Continual Learning from Multi-Label Drifting Data Streams. Neurocomputing, 442:10-25, https://www.sciencedirect.com/science/article/abs/pii/S0925231221002782 IF: 5.72 (Q1 rank)

Srivastava A, Cano A, 2021. Analysis and forecasting of rivers pH level using Deep Learning. Progress in Artificial Intelligence, https://link.springer.com/article/10.1007%2Fs13748-021-00270-2

Petri A, Bogaz B, Cano A, Barbon S, 2021. Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction. Sensors, 21(21):7333, https://www.mdpi.com/1424-8220/21/21/7333 IF: 3.58 (Q1 rank)

Belhadi A, Djenouri Y, Srivastava G, Cano A, Lin J, 2021. Hybrid Group Anomaly Detection for Sequence Data: Application to Trajectory Data Analytics. IEEE Transactions on Intelligent Transportation Systems, https://ieeexplore.ieee.org/document/9548779 IF: 6.49 (Q1 rank)

Djenouri Y, Belhadi H, Akli-Astouati K, Cano A, Lin J, 2021. An Ontology Matching Approach for Semantic Modeling: A Case Study in Smart Cities. Computational Intelligence, IF: 2.33

Cachi P, Ventura S, Cios KJ. 2021. CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks, Frontiers in Computational Neuroscience 15: 627567 https://www.frontiersin.org/articles/10.3389/fncom.2021.627567/abstract  IF: 2:38

Cranston DW, Yancey M, 2021. Vertex Partitions into an Independent Set and a Forest with Each Component Small. SIAM J. on Discrete Math. 35(3):1769-1791 https://doi.org/10.1137/21M1392280 IF: 0.755

Chatterjee P, Damevski K, Kraft NA, Pollock L, 2021. Automatically Identifying the Quality of Developer Chats for Post Hoc Use. ACM Transactions on Software Engineering and Methodology (TOSEM), https://doi.org/10.1145/3450503 IF: 2.67

Bui N, Pham N, Barnitz JJ, Zou Z, Nguyen P, Truong H, Kim T, Farrow N, Nguyen A, Xiao J, Deterding R, Dinh T, Vu T, 2021. eBP: an ear-worn device for frequent and comfortable blood pressure monitoring, Communications of the ACM, 64(8):118-125 https://doi.org/10.1145/3470446 IF 4.65 (Q1 rank)

Pham N, Dinh T, Kim T, Raghebi Z, Bui N, Truong H, Nguyen T, Banaei-Kashani F, Halbower A, Dinh T, Nguyen V, Vu T, 2021. Detection of Microsleep Events with a Behind-the-ear Wearable System, IEEE Transactions on Mobile Computing, 2021 (https://doi.org/10.1109/TMC.2021.3090829) IF 5.54 (Q1 rank)

Ahmed S, Xiao Y, Chung T, Fung C, Yung M, Yao D, 2021. Privacy Guarantees of BLE Contact Tracing: A Case Study on COVIDWISE. IEEE Computer Magazine (accepted). IF: 3.56

Sosnkowski A, Fung C, Ramkumar S, 2021. An analysis of Twitter users’ long term political view migration using cross-account data mining. Online Social Networks and Media 26:100177 https://www.sciencedirect.com/science/article/abs/pii/S2468696421000574 IF: 3.79

Pereira G, Ghosh P, Santos A, 2021. A Bridging Centrality Plugin for GEPHI and a Case Study for Mycobacterium Tuberculosis H37Rv. IEEE/ACM Trans Comput Biol Bioinform. 18(6):2741-2746 https://doi.org/10.1109/TCBB.2021.3120937  IF: 3.71 (Q1 rank)

Roy S, Ghosh P, 2021. Scalable and distributed strategies for socially distanced human mobility. Appl Netw Sci 6, 95 https://doi.org/10.1007/s41109-021-00437-9  IF: 2.33

Bose P, Srinivasan S, Sleeman WC IV, Palta J, Kapoor R, Ghosh P, 2021. A Survey on Recent Named Entity Recognition and Relationship Extraction Techniques on Clinical Texts. Applied Sciences 11(18):8319 https://doi.org/10.3390/app11188319  IF: 2.68

Barh D, Tiwari S, Gabriel Rodrigues Gomes L, Weener ME, Alzahrani KJ, Alsharif KF, Aljabali AAA, Tambuwala MM, Lundstrom K, Hassan SS, Serrano-Aroca Á, Takayama K, Ghosh P, Redwan EM, Silva Andrade B, Soares SC, Azevedo V, Uversky VN, 2021. Potential Molecular Mechanisms of Rare Anti-Tumor Immune Response by SARS-CoV-2 in Isolated Cases of Lymphomas. Viruses 13(10):1927 https://doi.org/10.3390/v13101927  IF: 5.05

Roy S, Ghosh N, Ghosh P, and Das SK, 2021. Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey. ACM Comput. Surv. 54(8):166 https://doi.org/10.1145/3468266  IF: 10.28 (Q1 rank)

Roy S, Biswas P, Ghosh P, 2021.Spatiotemporal tracing of pandemic spread from infection data. Sci Rep 11:17689  https://doi.org/10.1038/s41598-021-97207-5  IF: 4.38 (Q1 rank)

Rana P, Thai P, Dinh T, Ghosh P, 2021. Relevant and Non-Redundant Feature Selection for Cancer Classification and Subtype Detection. Cancers (Basel) 13(17):4297 https://doi.org/10.3390/cancers13174297  IF: 6.64 (Q1 rank)

Kumavath R, Paul S, Pavithran H, Paul MK, Ghosh P, Barh D, Azevedo V, 2021. Emergence of Cardiac Glycosides as Potential Drugs: Current and Future Scope for Cancer Therapeutics. Biomolecules 11(9):1275 https://doi.org/10.3390/biom11091275  IF: 4.88

da Silva JGV, Vieira AT, Sousa TJ, Viana MVC, Parise D, Sampaio B, da Silva AL, de Jesus LCL, de Carvalho PKRML, de Castro Oliveira L, Aburjaile FF, Martins FS, Nicoli JR, Ghosh P, Brenig B, Azevedo V, Gomide ACP, 2021. Comparative genomics and in silico gene evaluation involved in the probiotic potential of Bifidobacterium longum 51A. Gene 795:145781. https://doi.org/10.1016/j.gene.2021.145781 IF: 3.69

Nogueira WG, Jaiswal AK, Tiwari S, Ramos RTJ, Ghosh P, Barh D, Azevedo V, Soares SC, 2021. Computational identification of putative common genomic drug and vaccine targets in Mycoplasma genitalium. Genomics 113(4):2730-2743. https://doi.org/10.1016/j.ygeno.2021.06.011  IF: 5.74 (Q1 rank)

Roy S, Biswas P, Ghosh P, 2021. Effectiveness of Network Interdiction Strategies to Limit Contagion During a Pandemic, IEEE Access, 9:95862-95871 https://doi.org/10.1109/ACCESS.2021.3095252  IF: 3.37

Kapoor R, Sleeman WC, Nalluri JJ, Turner P, Bose P, Cherevko A, Srinivasan S, Syed K, Ghosh P, Hagan M and Palta JR, 2021. Automated data abstraction for quality surveillance and outcome assessment in radiation oncology. J Appl Clin Med Phys, 22:177-187. IF: 2.1

Kumavath R, Barh D, Andrade BS, Imchen M, Aburjaile FF, Ch A, Rodrigues DLN, Tiwari S, Alzahrani KJ, Góes-Neto A, Weener ME, Ghosh P, Azevedo V, 2021. The Spike of SARS-CoV-2: Uniqueness and Applications. Front Immunol. 12:663912. https://doi.org/10.3389/fimmu.2021.663912  IF: 7.56 (Q1 rank)

Silva Andrade B, Siqueira S, de Assis Soares WR, de Souza Rangel F, Santos NO, Dos Santos Freitas A, Ribeiro da Silveira P, Tiwari S, Alzahrani KJ, Góes-Neto A, Azevedo V, Ghosh P, Barh D, 2021. Long-COVID and Post-COVID Health Complications: An Up-to-Date Review on Clinical Conditions and Their Possible Molecular Mechanisms. Viruses 13(4):700. https://doi.org/10.3390/v13040700  IF: 5.05

Bose P, Roy S, Ghosh P, 2021. A Comparative NLP-Based Study on the Current Trends and Future Directions in COVID-19 Research, IEEE Access, 9:78341-78355 https://doi.org/10.1109/ACCESS.2021.3082108  IF: 3.37

Roy S, Ghosh P, 2021. A Comparative Study on Distancing, Mask and Vaccine Adoption Rates from Global Twitter Trends. Healthcare (Basel) 9(5):488. https://doi.org/10.3390/healthcare9050488  IF: 2.65

Roy S, Dutta R, Ghosh P, 2021. Identifying key indicators of job loss trends during COVID-19 and beyond. Soc Sci Humanit Open. 4(1):100163. https://doi.org/10.1016/j.ssaho.2021.100163 

Rodrigues DLN, Morais-Rodrigues F, Hurtado R, Dos Santos RG, Costa DC, Barh D, Ghosh P, Alzahrani KJ, Soares SC, Ramos R, Góes-Neto A, Azevedo V, Aburjaile FF, 2021. Pan-Resistome Insights into the Multidrug Resistance of Acinetobacter baumannii. Antibiotics (Basel) 10(5):596. https://doi.org/10.3390/antibiotics10050596 IF: 4.64

Franco EF, Rana P, Cruz A, Calderón VV, Azevedo V, Ramos RTJ, Ghosh P, 2021. Performance Comparison of Deep Learning Autoencoders for Cancer Subtype Detection Using Multi-Omics Data. Cancers (Basel) 13(9):2013. https://doi.org/10.3390/cancers13092013  IF: 6.64 (Q1 rank)

Syed K, Sleeman WC 4th, Hagan M, Palta J, Kapoor R, Ghosh P, 2021. Multi-View Data Integration Methods for Radiotherapy Structure Name Standardization. Cancers (Basel) 13(8):1796 https://doi.org/10.3390/cancers13081796  IF: 6.64 (Q1 rank)

Oliveira de Almeida M, Carvalho R, Figueira Aburjaile F, Malcher Miranda F, Canário Cerqueira J, Brenig B, Ghosh P, Ramos R, Kato RB, de Castro Soares S, Silva A, Azevedo V, Canário Viana MV, 2021. Characterization of the first vaginal Lactobacillus crispatus genomes isolated in Brazil. PeerJ 9:e11079 https://doi.org/10.7717/peerj.11079  IF: 2.98

Roy S, Cherevko A, Chakraborty S, Ghosh N, Ghosh P, 2021. Leveraging Network Science for Social Distancing to Curb Pandemic Spread, IEEE Access, 9:26196-26207 https://doi.org/10.1109/ACCESS.2021.3058206  IF: 3.37

Roy S, Dutta R, Ghosh P, 2021. Towards Dynamic lockdown strategies controlling pandemic spread under healthcare resource budget. Appl Netw Sci 6, 2 https://doi.org/10.1007/s41109-020-00349-0  IF: 2.33

Roy S, Biswas P, Ghosh P, 2021. Quantifying Mobility and Mixing Propensity in the Spatiotemporal Context of a Pandemic Spread, IEEE Transactions on Emerging Topics in Computational Intelligence, 5(3):321-331 https://doi.org/10.1109/TETCI.2021.3059007  IF: 8.28

Barh D, Tiwari S, Andrade BS, Weener ME, Góes-Neto A, Azevedo V, Ghosh P, Blum K, Ganguly NK, 2021. A novel multi-omics-based highly accurate prediction of symptoms, comorbid conditions, and possible long-term complications of COVID-19. Mol Omics 17(2):317-337. https://doi.org/10.1039/D0MO00189A  IF: 3.74

Roy S, Dutta R, Ghosh P, 2021. Optimal Time-Varying Vaccine Allocation Amid Pandemics With Uncertain Immunity Ratios, IEEE Access 9:15110-15121 https://doi.org/10.1109/ACCESS.2021.3053268  IF: 3.37

Roy S, Ghosh N, Ghosh P, Das SK, 2021. bioMCS 2.0: A distributed, energy-aware fog-based framework for data forwarding in mobile crowdsensing. Pervasive and Mobile Computing, 73:101381 http://doi.org/10.1016/j.pmcj.2021.101381 IF: 3.45

Orlovska I, Podolich O, Kukharenko O, Zaets I, Reva O, Khirunenko L, Zmejkoski D, Rogalsky S, Barh D, Tiwari S, Kumavath R, Góes-Neto A, Azevedo V, Brenig B, Ghosh P, de Vera JP, Kozyrovska N, 2021. Bacterial Cellulose Retains Robustness but Its Synthesis Declines After Exposure to a Mars-like Environment Simulated Outside the International Space Station. Astrobiology 21(6):706-717. https://doi.org/10.1089/ast.2020.2332  IF: 4.34 (Q1 rank)

Ghosh P, Pateras J, Rangachari V and Vaidya A, 2021. A Network Thermodynamic Analysis of Amyloid Aggregation along Competing Pathways. Applied Mathematics and Computation, 393:125778 https://doi.org/10.1016/j.amc.2020.125778 IF: 4.09 (Q1 rank)

Jaiswal AK, Tiwari S, Jamal SB, Oliveira LC, Sales-Campos H, Andrade-Silva LE, Oliveira CJF, Ghosh P, Barh D, Azevedo V, Soares SC, Rodrigues VR, da Silva MV, 2021. Reverse vaccinology and subtractive genomics approaches for identifying common therapeutics against Mycobacterium leprae and Mycobacterium lepromatosis. J Venom Anim Toxins Incl Trop Dis. 27:e20200027 https://doi.org/10.1590/1678-9199-jvatitd-2020-0027  IF: 2.83

Profeta R, Seyffert N, Tiwari S, Viana MVC, Jaiswal AK, Caetano AC, Bücker DH, Tavares de Oliveira L, Santos R, Gala-Garcia A, Kato RB, Padilha FF, Lima-Verde IB, Ghosh P, Barh D, Góes-Neto A, Figueiredo HCP, Soares SC, Meyer R, Brenig B, Ramos PIP, Azevedo V, Castro TLP, 2021. Comparative genomics with a multidrug-resistant Klebsiella pneumoniae isolate reveals the panorama of unexplored diversity in Northeast Brazil. Gene 26:145386. https://doi.org/10.1016/j.gene.2020.145386  IF: 3.69

Profeta R, Seyffert N, Tiwari S, Viana MVC, Jaiswal AK, Caetano AC, Bücker DH, de Oliveira LT, Santos R, Gala-Garcia A, Kato RB, Padilha FF, Lima-Verde IB, Ghosh P, Barh D, Góes-Neto A, Figueiredo HCP, Soares SC, Meyer R, Brenig B, Ramos PIP, Azevedo V, Castro TLP, 2021. Characterization of a new multidrug-resistant Brazilian K. pneumoniae isolate and 172 Klebsiella spp. sequenced strains: Genomic island, multilocus sequence typing and capsule locus dataset. Data Brief. 34:106746. https://doi.org/10.1016/j.dib.2021.106746 

Viana MVC, Profeta R, da Silva AL, Hurtado R, Cerqueira JC, Ribeiro BFS, Almeida MO, Morais-Rodrigues F, Soares SC, Oliveira M, Tavares L, Figueiredo H, Wattam AR, Barh D, Ghosh P, Silva A, Azevedo V, 2021. Taxonomic classification of strain PO100/5 shows a broader geographic distribution and genetic markers of the recently described Corynebacterium silvaticum. PLoS One 15(12):e0244210 https://doi.org/10.1371/journal.pone.0244210  IF: 3.24

Dablain D, Krawczyk B, Chawla N, 2021. DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2021.3136503 IF: 10.45 (Q1 rank)

Krawczyk B, 2021. Tensor decision trees for continual learning from drifting data streams. Machine Learning 110(11): 3015-3035 https://link.springer.com/article/10.1007%2Fs10994-021-06054-y IF: 2.94

Ghadermarzi S, Krawczyk B, Song J, Kurgan L, 2021. XRRpred: Accurate Predictor of Crystal Structure Quality from Protein Sequence. Bioinformatics, 37(23):4366-4374 IF: 6.94 (Q1 rank) 

Zhang F, Zhao B, Shi W, Li M, Kurgan L, 2021. DeepDISOBind: Accurate Prediction of RNA-, DNA- and Protein-binding Intrinsically Disordered Residues with Deep Multi-task Learning. Briefings in Bioinformatics, IF: 11.61 (Q1 rank)

Katuwawala A, Zhao B, Kurgan L, 2021. DisoLipPred: Accurate Prediction of Disordered Lipid Binding Residues in Protein Sequences with Deep Recurrent Networks and Transfer Learning. Bioinformatics, IF: 6.94 (Q1 rank) 

Zhao B, Katuwawala A, Oldfield CJ, Hu G, Wu Z, Uversky VN, Kurgan L, 2021. Intrinsic Disorder in Human RNA-binding Proteins. Journal of Molecular Biology, 433(21):167229 https://www.sciencedirect.com/science/article/pii/S0022283621004629 IF: 5.47 (Q1 rank)

Song R, Cao B, Peng Z, Oldfield CJ, Kurgan L, Wong K-C, Yang J, 2021. Accurate Sequence-based Prediction of Deleterious nsSNPs with Multiple Sequence Profiles and Putative Binding Residues. Biomolecules, 11(9):1337 https://www.mdpi.com/2218-273X/11/9/1337 IF: 4.88 (Q2 rank)

Hu G, Katuwawala A, Wang K, Wu Z, Ghadermarzi S, Gao J, Kurgan L, 2021. flDPnn: Accurate Intrinsic Disorder Prediction with Putative Propensities of Disorder Functions. Nature Communications, 12:4438 https://www.nature.com/articles/s41467-021-24773-7 IF: 14.92 (Q1 rank)

Zhang J, Ghadermarzi S, Katuwawala A, Kurgan L, 2021. DNAgenie: Accurate Prediction of DNA Type Specific Binding Residues in Protein Sequences. Briefings in Bioinformatics, 22(6):bbab336 IF: 11.61 (Q1 rank)

Katuwawala A, Ghadermarzi S, Hu G, Wu Z, Kurgan L, 2021. QUARTERplus: Accurate Disorder Predictions Integrated with Interpretable Residue-level Quality Assessment Scores. Computational and Structural Biotechnology Journal, 19:2597-2606 https://www.sciencedirect.com/science/article/pii/S2001037021001781 IF: 7.27 (Q1 rank)

Akbayrak IY, Caglayan SI, Durdagi S, Kurgan L, Uversky VN, Ulver B, Dervisoglu H, Haklidir M, Hasekioglu O, Coskuner-Weber O, 2021. Structures of MERS-CoV Macro Domain in Aqueous Solution with Dynamics: Impacts of Parallel Tempering Simulation Techniques and CHARMM36m and AMBER99SB Force Field Parameters. Proteins, 89(10):1289-1299 IF: 3.76

Necci M, Piovesan D, CAID Predictors (including Kurgan L), DisProt Curators, Tosatto S, 2021. Critical Assessment of Protein Intrinsic Disorder Prediction. Nature Methods, 18(5):472-481 https://www.nature.com/articles/s41592-021-01117-3  IF: 28.55 (Q1 rank)

Chen Z, Zhao P, Li C, Li F, Xiang D, Chen Y-Z, Akutsu T, Daly RJ, Webb GI, Zhao Q, Kurgan L, Song J, 2021. iLearnPlus: A Comprehensive and Automated Machine-learning Platform for Nucleic Acid and Protein Sequence Analysis, Prediction and Visualization. Nucleic Acids Research, 49(10):e60 IF: 16.97 (Q1 rank)

Klionski D, Kurgan L and 2917 co-authors, 2021. Guidelines for the Use and Interpretation of Assays for Monitoring Autophagy. Autophagy, 17(1):1-382 https://www.tandfonline.com/doi/full/10.1080/15548627.2020.1797280 IF: 16.02 (Q1 rank)

Seng S, Yang G, Li X, Ji H, and Luo C, 2021. Energy-efficient communications in unmanned aerial relaying systems, IEEE Transactions on Network Science and Engineering (TNSE), 8(4):2780-2791 https://ieeexplore.ieee.org/abstract/document/9372874 IF: 3.894 (Q1 rank)

Mahendran D, Luo C, McInnes BT, 2021. Review: Privacy-Preservation in the Context of Natural Language Processing. IEEE Access 9:147600-147612. https://ieeexplore.ieee.org/abstract/document/9592788. IF: 3.367

Vazquez S, Marino DL, Zafra E, Valdes M, Rodriguez-Andina J, Franquelo LG, Manic M, 2021. An Artificial Intelligence Approach for Real-Time Tuning of Weighting Factors in FCS-MPC for Power Converters, IEEE Transactions on Industrial Electronics, https://doi.org/10.1109/TIE.2021.3127046 IF 8.24 (Q1 rank)

Marino DL, Wickramasinghe CS, Tsouvalas B, Rieger C, and Manic M, 2021.  Data-Driven Correlation of Cyber and Physical Anomalies for Holistic System Health Monitoring, IEEE Access https://doi.org/10.1109/ACCESS.2021.3131274 IF 3.37

Marino DL, Wickramasinghe CS, Singh VK, Gentle J, Rieger C, and Manic M, 2021. The Virtualized Cyber-Physical Testbed for Machine Learning Anomaly Detection: A Wind Powered Grid Case Study, IEEE Access, 9:159475-159494, https://doi.org/10.1109/ACCESS.2021.3127169 IF 3.37

Wickramasinghe CS, Amarasinghe K, Marino DL, Rieger C, and Manic M, 2021. Explainable Unsupervised Machine Learning for Cyber-Physical Systems, IEEE Access, 9:131824-131843 https://doi.org/10.1109/ACCESS.2021.3112397 IF 3.37

Marino D and Manic M, 2021. Physics Enhanced Data-Driven Models with Variational Gaussian Processes, IEEE Open Journal of the Industrial Electronics Society, 2:252-265 https://doi.org/10.1109/OJIES.2021.3064820

Wickramasinghe CS, Marino DL, and Manic M, 2021. ResNet Autoencoders for Unsupervised Feature Learning From High-Dimensional Data: Deep Models Resistant to Performance Degradation, IEEE Access, 9:40511-40520 https://doi.org/10.1109/ACCESS.2021.3064819 IF 3.37

Lucia O, Martins J, Ibrahim Y, Umetani K, Gomes L, Hiraki E, Zeroug H, and Manic M, 2021. Industrial Electronics Education: Past, Present, and Future Perspectives, IEEE Industrial Electronics Magazine, 15(1):140-154 https://doi.org/10.1109/MIE.2020.3002488  IF 6.62 (Q1 rank)

Vaagensmith B, Kumar Singh V, Ivans R, Marino DL, Wickramasinghe CS, Lehmer J, Phillips T, Rieger C, Manic M, 2021.  Review of Design Elements within Power Infrastructure Cyber-Physical Test Beds as Threat Analysis Environments, Energies, 14(5):1409 https://doi.org/10.3390/en14051409

Farnsworth S, Gurdin G, Vargas J, Mulyar A, Lewinski N, McInnes BT, 2021. Extracting experimental parameter entities from scientific articles. Journal of Biomedical Informatics, https://doi.org/10.1016/j.jbi.2021.103970 IF: 6.37 (Q1 rank)

Lee K, Dobbins NJ, McInnes BT, Yetisgen M, Uzuner Ö, 2021. Transferability of neural network clinical deidentification systems. Journal of the American Medical Informatics Association, 28(12):2661-9 IF:4.50 (Q1 rank)

Mante J, Hao Y, Jett J, Joshi U, Keating K, Lu X, Nakum G, Rodriguez NE, Tang J, Terry L, Wu X, Yu E, Downie JS, McInnes BT, Nguyen MH, Sepulvado B, Young EM, Myers CJ, 2021. Synthetic Biology Knowledge System. ACS Synthetic Biology, 10(9):2276-85. IF: 5.11 (Q1 rank)

Tian S, Stevens R, McInnes BT, Lewinski NA, 2021. Machine assisted experimentation of extrusion-based bioprinting systems. Micromachines. 12(7):780. https://doi.org/10.3390/mi12070780 IF: 2.89

Mulyar A, Uzuner O, McInnes BT, 2021. MT-clinical BERT: scaling clinical information extraction with multitask learning. Journal of the American Medical Informatics Association, 28(10):2108-15 IF:4.50 (Q1 rank)

Mahendran D, Gurdin G, Lewinski N, Tang C, McInnes BT, 2021. Identifying chemical reactions and their associated attributes in patents. Frontiers in Research Metrics and Analytics, 6:688353 https://doi.org/10.3389/frma.2021.688353

Henry S, Wijesinghe DS, Myers A, McInnes BT, 2021. Using literature based discovery to gain insights into the metabolomic processes of cardiac arrest. Frontiers in Research Metrics and Analytics, 6:644728  https://doi.org/10.3389/frma.2021.644728

Olex AL, McInnes BT, 2021. Review of Temporal Reasoning in the Clinical Domain for Timeline Extraction: Where we are and where we need to be. Journal of Biomedical Informatics, 118:103784  https://doi.org/10.1016/j.jbi.2021.103784 IF: 6.32 (Q1 rank)

Soto M., Satterfield C, Fritz T, Murphy GC, Shepherd DC, and Kraft N, 2021. Observing and predicting knowledge worker stress, focus and awakeness in the wild. International Journal of Human-Computer Studies, 146:102560. IF: 3.63 (Q1 rank)

Pasandi H and Nadeem T, 2021. Towards a Learning-Based Framework for Self-Driving Design of Networking Protocols, IEEE Access, 9:34829-34844, https://doi.org/10.1109/ACCESS.2021.3061729 IF 3.37

Zhang H, Jin L, Ye C, 2021. An RGB-D Camera based Visual Positioning System for Assistive Navigation by a Robotic Navigation Aid, IEEE/CAA Journal of Automatica Sinica, 8(8):1389-1400 IF 6.17 (Q1 rank)

Broadbent A, Gharibian S, Zhou H-S, 2021. Towards Quantum One-Time Memories from Stateless Hardware. Quantum 5:429 https://doi.org/10.22331/q-2021-04-08-429 IF 6.78 (Q1 rank)

Ayub A, Yoo H, Ahmed I, 2021. Empirical Study of PLC Authentication Protocols in Industrial Control Systems. IEEE 15th Workshop on Offensive Technologies (WOOT’21), co-located with the 42nd IEEE Symposium on Security and Privacy and in cooperation with Usenix. https://doi.org/10.1109/SPW53761.2021.00058

Rais M, Li Y, Ahmed I. 2021. Spatiotemporal G-code modeling for secure FDM-based 3D printing. ACM/IEEE 12th International Conference on Cyber-Physical Systems (ICCPS '21). https://doi.org/10.1145/3450267.3450545

Panahi A, Saeedi S, Arodz T, 2021. Shapeshifter: a parameter-efficient Transformer using factorized reshaped matrices. Conference on Neural Information Processing Systems (NeurIPS'2021); https://papers.nips.cc/paper/2021/hash/09def3ebbc44ff3426b28fcd88c83554-Abstract.html (CORE A* rank)

Bokhari Y, Arodz T, 2021. PathMEx: Pathway-Based Mutual Exclusivity for Discovering Rare Cancer Driver Mutations. 21st International Conference on Computational Science (ICCS'2021); LNCS 12743:564-577; https://doi.org/10.1007/978-3-030-77964-1_43 (CORE A rank)

Zhang H, Arodz T, 2021. Learning Invariance in Deep Neural Networks. 21st International Conference on Computational Science (ICCS'2021); LNCS 12744:64-74; https://doi.org/10.1007/978-3-030-77967-2_6 (CORE A rank)

Hernandez SM, Erdag D, Bulut E, 2021. Towards Dense and Scalable Soil Sensing Through Low-Cost WiFi Sensing Networks.  IEEE 46th Conference on Local Computer Networks (LCN), Oct 4 (pp. 549-556) https://doi.org/10.1109/LCN52139.2021.9525003

Hernandez SM, Bulut E, 2021. Adversarial Occupancy Monitoring using One-Sided Through-Wall WiFi Sensing. IEEE International Conference on Communications (ICC), Jun 14 (pp. 1-6). https://doi.org/10.1109/ICC42927.2021.9500267

Chapnevis A, Güvenç İ, Njilla L, Bulut E, 2021. Collaborative Trajectory Optimization for Outage-aware Cellular-Enabled UAVs. IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), Apr 25 (pp. 1-6). https://doi.org/10.1109/VTC2021-Spring51267.2021.9448776

Krawczyk B, Cano, A, 2021. Locally Linear Support Vector Machines for Imbalanced Data Classification. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 616-628, https://link.springer.com/chapter/10.1007/978-3-030-75762-5_49 (CORE A rank)

Imran MM, Ciborowska A, Damevski K, 2021. Automatically Selecting Follow-up Questions for Deficient Bug Reports. 18th International Conference on Mining Software Repositories (MSR), https://doi.org/10.1109/MSR52588.2021.00029, (CORE A rank)

Chatterjee P, Damevski K, Pollock L, 2021. Automatic Extraction of Opinion-based Q&A from Online Developer Chats. 43rd International Conference on Software Engineering (ICSE), https://doi.org/10.1109/ICSE43902.2021.00115, (CORE A* rank)

Bose P, Sleeman W, Syed K, Hagan M, Palta J, Kapoor R, Ghosh P, 2021. Deep neural network models to automate incident triage in the radiation oncology incident learning system. 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB '21). Association for Computing Machinery, New York, NY, USA, Article 51, pp. 1-10 https://doi.org/10.1145/3459930.3469518

Roy S, Dutta R, Ghosh N, Ghosh P, 2021. Leveraging Periodicity to Improve Quality of Service in Mobile Software Defined Wireless Sensor Networks, 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), 2021, pp. 1-2, https://doi.org/10.1109/CCNC49032.2021.9369647

Roy S, Dutta R, Ghosh N, Ghosh P, 2021. Adaptive Motif-based Topology Control in Mobile Software Defined Wireless Sensor Networks, 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), 2021, pp. 1-6, https://doi.org/10.1109/CCNC49032.2021.9369601

Al Musawi AF, Ghosh P, 2021. Intrinsic and Simplified Complex Network Embedding Model. In: Kumar R., Mishra B.K., Pattnaik P.K. (eds) Next Generation of Internet of Things. Lecture Notes in Networks and Systems, vol 201. Springer, Singapore. https://doi.org/10.1007/978-981-16-0666-3_21

Korycki L, Krawczyk B, 2021. Concept Drift Detection from Multi-Class Imbalanced Data Streams. 37th IEEE International Conference on Data Engineering (ICDE), 1068-1079, https://ieeexplore.ieee.org/document/9458692 (CORE A* rank)

Korycki L, Krawczyk B, 2021. Streaming Decision Trees for Lifelong Learning. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), 502-518, https://link.springer.com/chapter/10.1007%2F978-3-030-86486-6_31 (CORE A rank)

Korycki L, Krawczyk B, 2021. Low-Dimensional Representation Learning from Imbalanced Data Streams. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 629-641, https://link.springer.com/chapter/10.1007%2F978-3-030-75762-5_50 (CORE A rank)

Krawczyk B, Cano, A, 2021. Locally Linear Support Vector Machines for Imbalanced Data Classification. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 616-628, https://link.springer.com/chapter/10.1007/978-3-030-75762-5_49 (CORE A rank)

Krawczyk B, 2021. Tensor Decision Trees for Continual Learning from Drifting Data Streams. 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 1-2, https://ieeexplore.ieee.org/document/9564150 (CORE A rank)

Krawczyk B, Bellinger C, Corizzo R, Japkowicz N, 2021. Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification. International Joint Conference on Neural Networks (IJCNN), 1-7 https://ieeexplore.ieee.org/document/9533379 (CORE A rank)

Korycki L, Krawczyk B, 2021. Class-Incremental Experience Replay for Continual Learning Under Concept Drift. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops), 3649-3658, https://openaccess.thecvf.com/content/CVPR2021W/CLVision/html/Korycki_Class-Incremental_Experience_Replay_for_Continual_Learning_Under_Concept_Drift_CVPRW_2021_paper.html

Wickramasinghe C, Marino D, and Manic M, 2021. Deep Embedded Clustering with ResNets,” in Proc. 14th International Conference on Human System Interaction, IEEE HSI 2021, Poland, July 8-10. 2020. pp. 1-6, DOI: https://doi.org/10.1109/HSI52170.2021.9538747

Mahendran D, McInnes BT, 2021. Extracting Adverse Drug Events from Clinical Notes. In American Medical Informatics Association Joint Summits on Translational Science, 420-429. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378605/

Smith J, French E, Cramer W, Uzuner Ӧ, McInnes BT, 2021. Pseudo-data generation for the extraction of Problems, Treatments and Tests. In American Medical Informatics Association Joint Summits on Translational Science, 575-584. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378614/

Mahendran D, Ranjan S, Tang J, Nguyen M, McInnes BT, 2021. BioCreative VII-Track 1: A BERT-based System for Relation Extraction in Biomedical Text. BioCreative VII Challenge Evaluation Workshop, 71 https://biocreative.bioinformatics.udel.edu/media/store/files/2021/Track1_pos_13_BC7_submission_155.pdf

Nukavarapu S, Ayyat M, and Nadeem T, 2021. iBranchy: An Accelerated edge inference platform for IoT Devices. The 2nd Workshop on Edge Computing and Communications (EdgeComm) in conjunction of Sixth ACM/IEEE Symposium on Edge Computing (SEC 2021), San Jose, CA, Dec., 2021.

Pasandi H, Amirpour H, Nadeem T, Trimmer C, 2021. Learning-driven MU-MIMO Grouping for Multi-User Multimedia Applications Over Commodity WiFi. The 1st ACM CoNEXT Workshop on Design, Deployment, and Evaluation of Network-assisted Video Streaming (ViSNext 2021) in conjunction with 17th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), Munich, Germany, Dec. 2021. https://doi.org/10.1145/3488662.3493828

Nukavarapu S and Nadeem T, 2021. Securing Edge-based IoT Networks with Semi-Supervised GANs. 5th IEEE International Workshop on Smart & Green Edge Computing and Networking (SmartEdge) in conjunction with the 2021 IEEE Conference on Pervasive Computing and Communications (PerCom), Kassel, Germany, 2021. https://doi.org/10.1109/PerComWorkshops51409.2021.9431112

Lusa Krug D, Bowman E, Barnett T, Pollock L, and Shepherd D, 2021. Code Beats: A Virtual Camp for Middle Schoolers Coding Hip Hop. 52nd ACM Technical Symposium on Computer Science Education, 397–403. (CORE A rank)

Zhang H and Ye C, 2021. Sampson Distance: A New Approach to Improving Visual-Inertial Odometry’s Accuracy, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 9184-9189. (CORE A rank)

Jin L, Zhang H, Ye C, 2021. W-ROMA: A Wearable Robotic Device for Assistive Navigation and Object Manipulation, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021, pp. 765-770. (CORE A rank)

Zhang B, Chen Y, Li J, Zhou Y, Thai P, Zhou H-S, Ren K, 2021. Succinct Scriptable NIZK via Trusted Hardware. ESORICS (1) 2021: 430-451 https://link.springer.com/chapter/10.1007%2F978-3-030-88418-5_21 (CORE A rank)

Lu Y, Zhang B, Zhou H-S, Liu W, Zhang L, Ren K, 2021. Correlated Randomness Teleportation via Semi-trusted Hardware - Enabling Silent Multi-party Computation. ESORICS (2) 2021: 699-720 https://link.springer.com/chapter/10.1007%2F978-3-030-88428-4_34 (CORE A rank)

Kurgan L, Li M, Li Y, 2021. Methods and Tools for Intrinsic Disorder Prediction and Their Application to Systems Medicine, In: Wolkenhauer O, (Ed.), Systems Medicine: Integrative Qualitative and Computational Approaches, vol.  1, pp 159-169, Elsevier, (ISBN 978-0-12-801238-3) https://www.sciencedirect.com/science/article/pii/B9780128012383113200

Shen X, Shen T, Afsar M R, Ye C, 2020. Motorized robotic walker guided by an image processing system for human walking assistance, US Patent 10,667,980, issued on June 2, 2020

CG Rieger, TR Mcjunkin, M Manic, K Amarasinghe, Systems And Methods For Control System Security, US Patent.No. 10,896,261, Publication date January 19, 2021.

Bhatt M, Mishra A, Kabir M, Blake-Gatto S, Rajendra R, Hoque M, Ahmed I, 2020. Hierarchy-Based File Fragment Classification. Machine Learning and Knowledge Extraction 2(3): 216-232; https://doi.org/10.3390/make2030012

Qasim S, Smith J, Ahmed I, 2020. Control Logic Forensics Framework using Built-in Decompiler of Engineering Software in Industrial Control Systems. Forensic Science International: Digital Investigation 33; https://doi.org/10.1016/j.fsidi.2020.301013

Bokhari Y, Alhareeri A, Arodz T, 2020. QuaDMutNetEx: a method for detecting cancer driver genes with low mutation frequency. BMC Bioinformatics 21:122; https://doi.org/10.1186/s12859-020-3449-2 IF: 3.242 (Q1 rank)

Yucel F, Yuksel M, and Bulut E, 2020. QoS-based Budget Constrained Stable Task Assignment in Mobile Crowdsensing, IEEE Transactions on Mobile Computing (TMC), doi: 10.1109/TMC.2020.2997280 https://ieeexplore.ieee.org/document/9099595 IF: 5.11 (Q1 rank)

Dhungana A, Bulut E, 2020. Energy balancing in mobile opportunistic networks with wireless charging: Single and multi-hop approaches, Ad hoc Networks,  doi: 10.1016/j.adhoc.2020.102342 https://www.sciencedirect.com/science/article/abs/pii/S1570870520306922 IF: 3.64 (Q1 rank)

Hernandez S, Bulut E, 2020. Using perceived direction information for anchorless relative indoor localization, Journal of Network and Computer Applications (JNCA), doi: 10.1016/j.jnca.2020.102714 https://www.sciencedirect.com/science/article/abs/pii/S1084804520301880 IF: 5.57 (Q1 rank)

Yucel F, Bulut E, 2020. User Satisfaction Aware Maximum Utility Task Assignment in Mobile Crowdsensing, Computer Networks, doi: 10.1016/j.comnet.2020.107156 https://www.sciencedirect.com/science/article/abs/pii/S1389128619311697 IF: 3.11

Chowdhury MU, Maeng SJ, Bulut E, Guvenc I, 2020. 3D Trajectory Optimization in UAV-Assisted Cellular Networks Considering Antenna Radiation Pattern and Backhaul Constraint, IEEE Transactions on Aerospace and Electronic Systems (TAES), doi: 10.1109/TAES.2020.2981233 https://ieeexplore.ieee.org/document/9037325 IF: 3.67 (Q1 rank)

Erdin E, Cebe M, Akkaya K, Solak S, Bulut E, Uluagac S, 2020. A Bitcoin Payment Network with Reduced Transaction Fees and Confirmation Times, Computer Networks, doi: 10.1016/j.comnet.2020.107098 https://www.sciencedirect.com/science/article/abs/pii/S1389128619308850 IF: 3.11

Djenouri Y, Djenouri D, Habbas z, Lin J, Michalak T, Cano A, 2020. When the Decomposition Meets the Constraint Satisfaction Problem. IEEE Access 8:207034-207043, https://ieeexplore.ieee.org/document/9260140 IF: 3.75 (Q1 rank)

Belhadi A, Djenouri Y, Srivastava G, Djenouri D, Cano A, Lin J, 2020. A Two-Phase Anomaly Detection Model for Secure Intelligent Transportation Ride-Hailing Trajectories. IEEE Transactions on Intelligent Transportation Systems, https://ieeexplore.ieee.org/document/9204632 IF: 6.32 (Q1 rank)

Belhadi A, Djenouri Y, Lin J, Cano A, 2020. A Data-Driven Approach for Twitter Hashtag Recommendation. IEEE Access 8:79182-79191, https://ieeexplore.ieee.org/document/9079518 IF: 3.75 (Q1 rank)

Belhadi A, Djenouri Y, Lin J, Cano A, 2020. Trajectory Outlier Detection: Algorithms, Taxonomies,Evaluation and Open Challenges. ACM Transactions on Management Information Systems 11(30):16, https://dl.acm.org/doi/10.1145/3399631

Belhadi A, Djenouri Y, Lin J, Zhang C, Cano A, 2020. Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem. IEEE Access 8:10569-10583, https://ieeexplore.ieee.org/document/8951154 IF: 3.75 (Q1 rank)

Belhadi A, Djenouri Y, Lin J, Cano A, 2020. A General-Purpose Distributed Pattern Mining System. Applied Intelligence 50:2647-2662, https://link.springer.com/article/10.1007/s10489-020-01664-w IF: 3.33 (Q1 rank)

Moyano JM, Gibaja EL, Cios KJ, Ventura S. 2020. Combining Multi-Label Classifiers Based on Projections of the Output Space Using Evolutionary Algorithms. Knowledge-Based Systems, 196:105770 10.1016/j.knosys.2020.105770 IF: 5.921 (Q1 rank)

Cranston DW and Yancey MP, 2020. Sparse Graphs are Near-bipartite. SIAM Journal on Discrete Math. SIAM Journal on Discrete Math. Vol. 34(3), 1725-1768.  IF: .755

Cranston DW and Li J, 2020. Circular Flows in Planar Graphs. SIAM Journal on Discrete Math. Vol. 34(1):497–519. IF: .755

Choi I, Cranston DW, and Pierron T, 2020. Degeneracy and Colorings of Squares of Planar Graphs without 4-Cycles. Combinatorica 40(5):625-653.  IF: 1.143

Ciborowska A, Damevski K, 2020. Recognizing Developer Activity Based on Joint Modeling of Code and Command Interactions. IEEE Access 8:211653-211664, https://ieeexplore.ieee.org/document/9268948 IF: 3.75 (Q1 rank)

Bui N, Pham N, Truong H, Nguyen P,  Xiao J, Deterding R, Dinh TN, Vu T, 2020. eBP: Frequent and Comfortable Blood Pressure Monitoring from Inside Human’s Ears, GetMobile: Mobile Computing and Communications, SIGMOBILE, 2020, https://dl.acm.org/doi/abs/10.1145/3400713.3400721

Bu N, Nguyen A, Nguyen P, Truong H, Ashok A, Dinh TN, Deterding R, Vu T, 2020. Smartphone-Based SpO2 Measurement by Exploiting Wavelengths Separation and Chromophore Compensation, ACM Transactions on Sensor Networks (TOSN). https://dl.acm.org/doi/abs/10.1145/3360725 IF: 2.47

Huang S, Liu Y, Fung C, He R, Zhao Y, Yang H, Luan Z, 2020. HitAnomaly: Hierarchical Transformers for Anomaly Detection in System Log. IEEE Transactions on Network and Service Management. https://ieeexplore.ieee.org/abstract/document/9244088 IF: 3.9

Yu H, Yang J, Fung C, 2020. Fine-grained Cloud Resource Provisioning for Virtual Network Function. IEEE Transactions on Network and Service Management. https://ieeexplore.ieee.org/abstract/document/9060987 IF: 3.9

El-Latif AA Abd, Abd-El-Atty B, Mazurczyk W, Fung C, 2020. Secure data encryption based on quantum walks for 5G Internet of Things scenario. IEEE Transactions on Network and Service Management 17 (1), 118-131. https://ieeexplore.ieee.org/abstract/document/8972594. IF: 3.9

Roy S, Dutta R, Ghosh P, 2020. Recreational and philanthropic sectors are the worst-hit US industries in the COVID-19 aftermath. Elsevier Social Science and Humanities, 3:1. https://doi.org/10.1016/j.ssaho.2020.100098  IF: 1.03

Carvalho, R, Aburjaile, F, Viana, MC, Nascimento, A, Souza-Chartone, E, Jesus, LD, Zamyatnin, A, Brenig, B, Barh, D, Ghosh, P, Góes-Neto, A, Soares, S, Ramos, R, Pinto, A, Azevedo, V, 2020. Genomic characterization of multidrug-resistant Escherichia coli BH100 sub-strains. Frontiers in Microbiology. https://www.frontiersin.org/articles/10.3389/fmicb.2020.549254/abstract  IF: 4.24 (Q1 rank)

Barh D, Tiwari S, Azevedo V, Góes-Neto A, Gromiha M and Ghosh P, 2020. Multi-omics-based identification of SARS-CoV-2 infection biology and candidate drugs against COVID-19. Computers in Biology and Medicine, 126:104051. https://doi.org/10.1016/j.compbiomed.2020.104051 IF: 3.43 (Q1 rank)

Roy S, Ghosh P, 2020. Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking. PLoS ONE 15(10): e0241165. https://doi.org/10.1371/journal.pone.0241165  IF: 2.74

Syed K, Sleeman W, Hagan M, Palta J, Kapoor R, Ghosh, P, 2020. Automatic Incident Triage in Radiation Oncology Incident Learning System. Healthcare, 8, 272. https://doi.org/10.3390/healthcare8030272 IF: 1.92

Imchen M, Moopantakath J, Kumavath R, Barh D, Tiwari S, Ghosh P and Azevedo V, 2020. Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance. Front. Genet. 11:563975. doi: 10.3389/fgene.2020.563975 IF: 3.26

Reddy D, Kumavath R, Barh D, Azevedo V, Ghosh P, 2020. Anticancer and Antiviral Properties of Cardiac Glycosides: A Review to Explore the Mechanism of Actions. Molecules, 25(16):3596. doi:10.3390/molecules25163596 IF: 3.06

Leite EL, Oliveira AF Jr, Carmo FLRD, Berkova N, Barh D, Ghosh P, Azevedo V, 2020. Bacteriocins as an alternative in the treatment of infections by Staphylococcus aureus. An Acad Bras Cienc. 92(suppl 2):e20201216. doi: 10.1590/0001-3765202020201216. PMID: 33084762.

Barh D, Silva Andrade B, Tiwari S, Giovanetti M, Góes-Neto A, Alcantara LCJ, Azevedo V, Ghosh P, 2020. Natural selection versus creation: a review on the origin of SARS-COV-2. Infez Med. 28(3):302-311. PMID: 32920565.

Franco EF, Rana P, Queiroz Cavalcante AL, da Silva AL, Cybelle Pinto Gomide A, Carneiro Folador AR, Azevedo V, Ghosh P, TJ Ramos R, 2020. Co-Expression Networks for Causal Gene Identification Based on RNA-Seq Data of Corynebacterium pseudotuberculosis. Genes 11, 794. IF: 3.33

Sleeman Iv WC, Nalluri J, Syed K, Ghosh P, Krawczyk B, Hagan M, Palta J, Kapoor R, 2020. A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels. J Biomed Inform. 109:103527. doi: 10.1016/j.jbi.2020.103527. Epub 2020 Aug 8. PMID: 32777484. IF: 3.53

Araújo CL, Blanco I, Souza L, Tiwari S, Pereira LC, Ghosh P, Azevedo V, Silva A, Folador A, 2020. In silico functional prediction of hypothetical proteins from the core genome of Corynebacterium pseudotuberculosis biovar ovis. PeerJ 8:e9643. doi: 10.7717/peerj.9643. PMID: 32913672; PMCID: PMC7456259. IF: 2.38

Syed K, Sleeman W, Soni P, Hagan M, Palta J, Kapoor R, Ghosh P, 2020. Machine-Learning Models for Multicenter Prostate Cancer Treatment Plans. J Comput Biol. doi: 10.1089/cmb.2020.0188. PMID: 32985908. IF: 1.1

Roy S, Ghosh P, Barua D, Das SK, 2020. Motifs enable communication efficiency and fault-tolerance in transcriptional networks. Sci Rep 10, 9628 https://doi.org/10.1038/s41598-020-66573-x JCR: Q1; IF: 3.99

Barh D, Tiwari S, Silva Andrade B, Giovanetti M, Almeida Costa E, Kumavath R, Ghosh P, Góes-Neto A, Carlos Junior Alcantara L, Azevedo V, 2020. Potential chimeric peptides to block the SARS-CoV-2 spike receptor-binding domain. F1000Res. 9:576. doi: 10.12688/f1000research.24074.1. PMID: 32802318; PMCID: PMC7411520.

Silva Andrade B, Ghosh P, Barh D et al, 2020. Computational screening for potential drug candidates against the SARS-CoV-2 main protease. F1000Research 9:514 (https://doi.org/10.12688/f1000research.23829.1)

Podolich O, […], Ghosh P, Barh D, Góes-Neto A, Azevedo V, de Vera JP, Kozyrovska N, 2020. Fitness of Outer Membrane Vesicles From Komagataeibacter intermedius Is Altered Under the Impact of Simulated Mars-like Stressors Outside the International Space Station. Front Microbiol. 11:1268. doi: 10.3389/fmicb.2020.01268. PMID: 32676055; PMCID: PMC7333525. JCR: Q1; IF: 4.24

Syed K, Sleeman IV W, Ivey K, Hagan M, Palta J, Kapoor R, Ghosh P, 2020. Integrated Natural Language Processing and Machine Learning Models for Standardizing Radiotherapy Structure Names. Healthcare 8, 120. IF: 1.92

Ghosh P, Rana P, Rangachari V, Saha J, Steen E, Vaidya A, 2020. A game-theoretic approach to deciphering the dynamics of amyloid-β aggregation along competing pathways. R Soc Open Sci. 7(4):191814. doi: 10.1098/rsos.191814. PMID: 32431878; PMCID: PMC7211858. IF: 2.65

Phillips MH, Serra LM, Dekker A, Ghosh P, Luk SMH, Kalet A, Mayo C, 2020. Ontologies in radiation oncology. Phys Med. 72:103-113. doi: 10.1016/j.ejmp.2020.03.017. PMID: 32247963. IF: 2.48

Santos RG, […], Ghosh P, Seyffert N, Azevedo V, 2020. Complete genome analysis of Glutamicibacter creatinolyticus from mare abscess and comparative genomics provide insight of diversity and adaptation for Glutamicibacter. Gene 741:144566. doi: 10.1016/j.gene.2020.144566. PMID: 32171826. IF: 2.98

Jaiswal AK, Tiwari S, Jamal SB, Oliveira LC, Alves LG, Azevedo V, Ghosh P, Oliveira CJ, Soares SC, 2020. The pan-genome of Treponema pallidum reveals differences in genome plasticity between subspecies related to venereal and non-venereal syphilis. BMC Genomics 21, 33 https://doi.org/10.1186/s12864-019-6430-6 IF: 3.6

Sleeman WC, Krawczyk B, 2020. Multi-class imbalanced big data classification on Spark. Knowledge-Based Systems doi: 10.1016/j.knosys.2020.106598 https://www.sciencedirect.com/science/article/pii/S0950705120307279 IF: 5.92 (Q1 rank)

Koziarski M, Wozniak M, Krawczyk B, 2020. Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise. Knowledge-Based Systems 204: 106223 https://www.sciencedirect.com/science/article/pii/S0950705120304330 IF: 5.92 (Q1 rank)

Sleeman WC, Nalluri J, Syed K, Ghosh P, Krawczyk B, Hagan M, Palta J, Kapoor R, 2020. A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels. Journal of Biomedical Informatics 109: 103527 https://www.sciencedirect.com/science/article/pii/S1532046420301556 IF: 3.53

Katuwawala A, Kurgan L, 2020. Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins. Biomolecules 10(12):1636; https://doi.org/10.3390/biom10121636 IF: 4.08

Zhao B, Katuwawala A, Oldfield CJ, Dunker K, Faraggi E, Gsponer J, Kloczkowski A, Malhis N, Mirdita M, Obradovic Z, Söding J, Steinegger M, Zhou Y, Kurgan L, 2020. DescribePROT: Database of Amino Acid-level Protein Structure and Function Predictions. Nucleic Acids Research, IF: 11.50 (Q1 rank)

Zhang F, Shi W, Zhang J, Zeng M, Li M, Kurgan L, 2020. PROBselect: Accurate Prediction of Protein-Binding Residues from Proteins Sequences via Dynamic Predictor Selection. Bioinformatics 36: i735–i744 IF: 5.61 (Q1 rank)

Peng Z, Xing Q, Kurgan L, 2020. APOD: Accurate Sequence-Based Predictor of Disordered Flexible Linkers. Bioinformatics 36:i754–i761, https://doi.org/10.1093/bioinformatics/btaa808 IF: 5.61 (Q1 rank)

Zhao B, Katuwawala A, Uversky VN, Kurgan L, 2020. IDPology of the Living Cell: Intrinsic Disorder in the Subcellular Compartments of the Human Cell. Cellular and Molecular Life Sciences https://doi.org/10.1007/s00018-020-03654-0 IF: 6.50 (Q1 rank)

Zhang J, Ghadermarzi S, Kurgan L, 2020. Prediction of Protein-Binding Residues: Dichotomy of Sequence-Based Methods Developed Using Structured Complexes Versus Disordered Proteins. Bioinformatics 36(18):4729-4738 IF: 5.61 (Q1 rank)

Gao J, Wei H, Cano A, Kurgan L, 2020. PSIONplus^m Server for Accurate Multi-Label Prediction of Ion Channels and Their Types. Biomolecules 10(6):876 https://www.mdpi.com/2218-273X/10/6/876 IF: 4.08

Liu L, Kurgan L, Wu FX, Wang J, 2020. Attention Convolutional Neural Network for Accurate Segmentation and Quantification of Lesions in Ischemic Stroke Disease. Medical Image Analysis 65:101791 https://doi.org/10.1016/j.media.2020.101791 IF: 11.15 (Q1 rank)

Chen H, Li F, Wang L, Jin Y, Chi CH, Kurgan L, Song J, Shen J, 2020. Systematic Evaluation of Machine Learning Methods for Identifying Human–Pathogen Protein–Protein Interactions. Briefings in Bioinformatics IF: 8.99 (Q1 rank)

Barik A, Katuwawala A, Hanson J, Paliwal K, Zhou Y, Kurgan L, 2020. DEPICTER: Intrinsic Disorder and Disorder Function Prediction Server. Journal of Molecular Biology 432(11):3379-3387 https://www.sciencedirect.com/science/article/pii/S0022283619307399 IF: 4.76 (Q1 rank)

Zhang J, Li W, Zeng M, Meng X, Kurgan L, Wu FX, Li M, 2020. NetEPD: A Network-Based Essential Protein Discovery Platform. Tsinghua Science and Technology https://ieeexplore.ieee.org/document/8954872 25(4):542-552 IF: 1.33

Wang K, Hu G, Wu Z, Su H, Yang J, Kurgan L, 2020. Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type. International Journal of Molecular Sciences 21(18):6879 https://www.mdpi.com/1422-0067/21/18/6879 IF: 4.56 (Q1 rank)

Yu L, Guo Y, Wang Q, Luo C, Liao W, Li M, and Li P, 2020. Spectrum Availability Prediction for Cognitive Radio Communications: A DCG Approach. IEEE Trans. Cognitive Communications and Networking. 6(2): 476-485. https://ieeexplore.ieee.org/document/8998400 , IF: 4.574

Ji T, Luo C, Guo Y, Wang Q, Yu L, and Li P, 2020. Community Detection in Online Social Networks: A Di_erentially Private and Parsimonious Approach. IEEE Trans. Computational Social Systems. 7(1): 151 - 163. https://ieeexplore.ieee.org/document/8999786, IF: 3.29

Luo C, Ji J, Wang Q, Chen X, and Li P, 2020. Channel State Information Prediction for 5G Wireless Communications: A Deep Learning Approach. IEEE Trans. Network Science and Engineering. 7(1): 227-236. https://ieeexplore.ieee.org/document/8395053, IF: 5.213

X. Yan, Y. Ye, X. Qiu, M. Manic and H. Yu, "CMIB: Unsupervised Image Object Categorization in Multiple Visual Contexts," in IEEE Transactions on Industrial Informatics, vol. 16, no. 6, pp. 3974-3986, June 2020. https://ieeexplore.ieee.org/document/8823028 IF: 8.480

Cuffy, C, Hagiwara N, Vrana S, McInnes BT, 2020. Measuring the quality of patient-physician communication. Journal of Biomedical Informatics. 12:103589. https://www.sciencedirect.com/science/article/abs/pii/S1532046420302185  IF: 3.526

Sutphin, C, Lee K, Yepes AJ, Uzuner Ö, McInnes BT, 2020. Adverse drug event detection using reason assignments in FDA drug labels. Journal of Biomedical Informatics 110:103552. https://www.sciencedirect.com/science/article/abs/pii/S1532046420301805  IF: 3.526

N. Ritschel, V. Kovalenko, R. Holmes, R. Garcia, Shepherd DC, 2020. Comparing Block-based Programming Models for Two-armed Robots, IEEE Transactions on Software Engineering, https://doi:10.1109/TSE.2020.3027255 (CORE A*), IF: 3.31 (Q1 rank)

V. Garousi, Shepherd DC, K. Herkiloglu, 2020. Successful Engagement of Practitioners and Software Engineering Researchers: Evidence From 26 International Industry–Academia Collaborative Projects, IEEE Software, vol. 37, no. 6, pp. 65-75, Nov.-Dec. 2020, doi: https://10.1109/MS.2019.2914663. IF: 2.945

Jin L, Zhang H, Ye C, 2020. Camera Intrinsic Parameters Estimation by Visual Inertial Odometry for a Mobile Phone with Application to Assisted Navigation. IEEE/ASME Transactions on Mechatronics 25(4): 1803-1811 https://ieeexplore.ieee.org/document/9099599 IF: 5.673 (Q1 rank)

Zhang H and Ye C, 2020. Plane-Aided Visual-Inertial Odometry for 6-DOF Pose Estimation of a Robotic Navigation Aid. IEEE Access 8: 90042-90051 https://ieeexplore.ieee.org/document/9091872 IF: 3.745 (Q1 rank)

Shen T, Afsar M R, Zhang, H, Ye C, Shen X, 2020. A 3D Computer Vision-Guided Robotic Companion for Non-Contact Human Assistance and Rehabilitation. Journal of Intelligent & Robotics Systems 100:911-923 https://link.springer.com/article/10.1007/s10846-020-01258-1 IF: 2.259

Dana Dachman-Soled, Feng-Hao Liu, Elaine Shi, Hong-Sheng Zhou, 2020.Locally Decodable and Updatable Non-malleable Codes and Their Applications. J. Cryptol. 33(1): 319-355 (CORE A* rank) https://link.springer.com/article/10.1007/s00145-018-9306-z

Zhang H, Gao X, Unterman J, Arodz T, 2020. Approximation capabilities of Neural ODEs and Invertible Residual Networks. 37th International Conference on Machine Learning (ICML'2020); PMLR 119:11086-11095; http://proceedings.mlr.press/v119/zhang20h.html (CORE A* rank)

Panahi A, Saeedi S, Arodz T, 2020. word2ket: space-efficient word embeddings inspired by quantum entanglement. 8th International Conference on Learning Representations (ICLR'20) https://iclr.cc/virtual_2020/poster_HkxARkrFwB.html (CORE A* rank)

Arodz T, 2020. Generalized quantum Deutsch-Jozsa algorithm. 20th International Conference on Computational Science (ICCS'2020); LNCS 12142:465-472; https://link.springer.com/chapter/10.1007%2F978-3-030-50433-5_36 (CORE A rank)

Arodz T, 2020. Biological network visualization for targeted proteomics based on mean first-passage time in semi-lazy random walks. 20th International Conference on Computational Science (ICCS'2020); LNCS 12139:539-549; https://link.springer.com/chapter/10.1007/978-3-030-50420-5_40 (CORE A rank)

Chapnevis A, Guvenc I, Bulut E, 2020. Traffic Shifting based Resource Optimization in Aggregated IoT Communication", 45th IEEE Local Computer Networks (LCN), Nov 16-19, 2020. (Core A rank) http://www.people.vcu.edu/~ebulut/LCN20-IoT.pdf

Yucel F, Bulut E, 2020. Time-dependent Stable Task Assignment in Participatory Mobile Crowdsensing, 45th IEEE Local Computer Networks (LCN), Nov 16-19, 2020. http://www.people.vcu.edu/~ebulut/LCN20-crowdsensing.pdf

Yucel F, Bhuyan A, Bulut E, 2020. Secure, Resilient and Stable Resource Allocation for D2D-based V2X Communication, IEEE Resilience Week, Oct, 2020. https://ieeexplore.ieee.org/document/9241290

Bulut E, Dhungana A, 2020. Social-Aware Energy Balancing in Mobile Opportunistic Networks, IEEE 16th International Conference on Distributed Computing in Sensor Systems (DCOSS) - 2nd International Workshop on Wirelessly Powered Systems and Networks (WPSN), July 15-17, 2020. https://ieeexplore.ieee.org/abstract/document/9183404

Dhungana A, Bulut E, 2020. Opportunistic Wireless Crowd Charging of IoT Devices from Smartphones, IEEE 16th International Conference on Distributed Computing in Sensor Systems (DCOSS) - 2nd International Workshop on Wirelessly Powered Systems and Networks (WPSN), July 15-17, 2020. https://ieeexplore.ieee.org/abstract/document/9183664

Hernandez S, Bulut E, 2020. Lightweight and Standalone IoT based WiFi Sensing for Active Repositioning and Mobility, 21st IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), August 31 - September 03, 2020, Cork, Ireland. https://ieeexplore.ieee.org/document/9217780 (Core A rank)

Hernandez S, Bulut E, 2020. Performing WiFi Sensing with Off-the-shelf Smartphones, IEEE International Conference on Pervasive Computing and Communications (Percom) Workshops, 23-27 March 2020, Austin, TX, USA. (Best demo award) https://ieeexplore.ieee.org/document/9156194

Perez J, [...], Cano A, et. al., 2020. An Endocrine and metabolic interactomic approach to identify novel diagnostic/prognostic biomarkers and therapeutic targets in gliomas. 22nd European Congress of Endocrinology, https://www.endocrine-abstracts.org/ea/0070/ea0070aep529.htm

Moyano JM, Gibaja EL, Cios KJ, Ventura S. 2020. Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming. 2020 IEEE Congress on Evolutionary Computation (CEC), Glasgow, United Kingdom, pp. 1-8, DOI: 10.1109/CEC48606.2020.9185661

Cachi PG, Ventura S, Cios KJ. 2020. Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization. 18th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, Lisbon. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1239, Springer https://link.springer.com/chapter/10.1007%2F978-3-030-50153-2_57

Pham N, Dinh T, Ragheb Zi, Kim T, Bui N, Nguyen P,  Truong H, Banaei-Kashani F, Halbower A, Dinh TN, Vu T, 2020. WAKE: a behind-the-ear wearable system for microsleep detection, 18th International Conference on Mobile Systems, Applications, and Services (MOBISYS’20), (Top CSRankings) https://dl.acm.org/doi/abs/10.1145/3386901.3389032

Truong H, Bui N, Raghebi Z, Ceko M, Pham N, Nguyen P, Nguyen A, Kim T, Siegfried K, Stene E, Tvrdy T, Weinman L, Payne T, Burke D, Dinh TN, D'Mello S, Banaei-Kashani F, Wager T, Goldstein P, Vu T, 2020. Painometry: wearable and objective quantification system for acute postoperative pain, 18th International Conference on Mobile Systems, Applications, and Services (MOBISYS’20), (Top CSRankings), https://dl.acm.org/doi/abs/10.1145/3386901.3389022

Moyano JM, Gibaja EL, Cios KJ, Ventura S, 2020. Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms. 24^th European Congress on Artificial Intelligence, ECAI 2020, Santiago de Compostela, Spain, pp. 1379-1386, DOI: 10.3233/FAIA200242

Bonato A, Cranston DW, Huggan M, Marbach T, Mutharasan R, 2020.  The Iterated Local Directed Transitivity Model for Social Networks.  17th Workshop on Algorithms and Models for the Web Graph. Algorithms and Models for the Web Graph, 111-123.  SGH Warsaw School of Economics, Warsaw, Poland (September 21-25, 2020).  Springer: https://link.springer.com/chapter/10.1007/978-3-030-48478-1_8

Chatterjee P, Damevski K, Kraft NA, Pollock L, 2020. Software-related Slack Chats with Disentangled Conversations. 17th International Conference on Mining Software Repositories (MSR 2020), 588-592 Seoul, Korea, June 2020 https://dl.acm.org/doi/10.1145/3379597.3387493 (CORE A rank)

Huang S, Liu Y, Fung C, He R, Zhao Y, Yang H, Luan Z, 2020. Transfer Log-based Anomaly Detection with Pseudo Labels. 2020 16th International Conference on Network and Service Management (CNSM), 1-5 https://ieeexplore.ieee.org/abstract/document/9269069 (CORE rank B)

Fung C, McCormick B, 2020. An Effective Policy Sharing Mechanism for Smart Home Networks. 2020 16th International Conference on Network and Service Management (CNSM), 1-7. https://ieeexplore.ieee.org/abstract/document/9269110. (CORE rank B)

Fung C, Pillai Y, 2020. A Privacy-Aware Collaborative DDoS Defence Network. NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, 1-5. https://ieeexplore.ieee.org/abstract/document/9110330. (CORE rank B)

Huang S, Liu Y, Fung C, He R, Zhao Y, Luan H Z. Paddy, 2020. An Event Log Parsing Approach using Dynamic Dictionary. NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, 1-8. https://ieeexplore.ieee.org/abstract/document/9110435. (CORE rank B)

Huang S, Liu Y, Fung C, An W, He R, Zhao Y, Yang H, Luan Z, 2020. A Gated Few-shot Learning Model For Anomaly Detection. 2020 International Conference on Information Networking (ICOIN), 505-509. https://ieeexplore.ieee.org/abstract/document/9016599. (CORE rank B)

Ramkumar S, Sosnkowski A, Coffman D, Fung C, Levy J, 2020. An Analysis of Twitter Users’ Political Views Using Cross-Account Data Mining. Smart Technologies in Data Science and Communication, 115-121. https://link.springer.com/chapter/10.1007/978-981-15-2407-3_16.

Rana P, Bose P, Vaidya A, Rangachari V, Ghosh P, 2020. Global fitting and parameter identifiability for amyloid-β aggregation models with competing pathways. IEEE BIBE 2020, pp. 1-8.

Roy S, Ghosh N, Ghosh P, Das SK, 2020. BioMCS: A Bio-inspired Collaborative Data Transfer Framework over Fog Computing Platforms in Mobile Crowdsensing. 21st International Conference on Distributed Computing and Networking (ICDCN 2020). Association for Computing Machinery, New York, NY, USA, Article 23, 1–10. DOI:https://doi.org/10.1145/3369740.3369788

Korycki L, Krawczyk B, 2020. Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams. International Joint Conference on Neural Networks (IJCNN 2020): 1-8 Glasgow, United Kingdom, July 2020 https://ieeexplore.ieee.org/document/9207118 (CORE rank A)

Ghadermarzi S, Katuwawala A, Oldfield CJ, Barik A, Kurgan L, 2020. Disordered Function Conjunction: On the In-silico Function Annotation of Intrinsically Disordered Regions. Pacific Symposium on Biocomputing (PSB’2020) 25:171-182, Big Island of Hawaii, USA, January 2020 https://www.worldscientific.com/doi/abs/10.1142/9789811215636_0016

Kurgan L, Radivojac P, Sussman J, Dunker K, 2020. On the Importance of Computational Biology and Bioinformatics to the Origins and Rapid Progression of the Intrinsically Disordered Proteins Field. Pacific Symposium on Biocomputing (PSB’2020) 25:149-158, Big Island of Hawaii, USA, January 2020 https://www.worldscientific.com/doi/10.1142/9789811215636_0014

Seng S, Yang G, Li X, Ji H, and Luo C, 2020. Energy-Efficient Communications in Solar-Powered Unmanned Aerial Systems. IEEE Global Communications Conference (GLOBECOM'20), Taipei, Taiwan, Dec. 7-11, 2020. (to appear in IEEE Xplore) (CORE rank B)

J. Ulrich, C. Rieger, J. Grandio and M. Manic, 2020. Cyber-Physical Architecture for Automated Responses (CyPhAAR) Using SDN in Adversarial OT Environments, 2020 Resilience Week (RWS), Salt Lake City, ID, USA, 2020, pp. 55-63, doi: 10.1109/RWS50334.2020.9241285, https://ieeexplore.ieee.org/document/9241285.

D. Marino, J. Grandio, C. Wickramasinghe, K. Schroeder, K. Bourne,  A.V. Filippas, M. Manic, 2020. AI Augmentation for Trustworthy AI: Augmented Robot Teleoperation, 13th International Conference on Human System Interaction, IEEE HSI 2020, Tokyo, Japan, June 6-8. 2020. https://ieeexplore.ieee.org/document/9142659

C. Wickramasinghe, D. Marino, J. Grandio, and M. Manic, 2020. Trustworthy AI Development Guidelines for Human System Interaction. 13th International Conference on Human System Interaction, IEEE HSI 2020, Tokyo, Japan, June 6-8. 2020. https://ieeexplore.ieee.org/document/9142644

Mahendran D, Gurdin G, Lewinski NA, Tang C, McInnes BT, 2020. NLPatVCU CLEF 2020 ChEMU Shared Task System Description. Conference and Labs of the Evaluation Forum (CLEF) 2020 Working Notes. http://ceur-ws.org/Vol-2696/paper_215.pdf

Gurdin G, Vargas JA, Maffey LG, Olex AL, Lewinski NA, McInnes BT, 2020. Analysis of Inter-Domain and Cross-Domain Drug Review Polarity Classification. American Medical Informatics Association Summits on Translational Science. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233089/

Olex AL, DiazGranados D, McInnes BT, Goldberg S, 2020. Local Topic Mining for Reflective Medical Writing.  American Medical Informatics Association Summits on Translational Science. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233034/

Mahendran D,  Lewis C,  McInnes BT, 2020. NLP@ VCU: Identifying adverse effects in English tweets for unbalanced data. Fifth Social Media Mining for Health  Applications Workshop & Shared Task. https://www.aclweb.org/anthology/2020.smm4h-1.29.pdf Emad Aghajani, Csaba Nagy, Mario Linares-Vásquez,

Pasandi H.B., Nadeem T, 2020. Mac Protocol Design Optimization using Deep Learning. 2020 IEEE International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (pp. 709-715), February, 2020. https://ieeexplore.ieee.org/document/9065254

Pasandi H.B., Nadeem T, 2020. CONVINCE: Collaborative Cross-Camera Video Analytics at the Edge. 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops, March 2020. https://ieeexplore.ieee.org/document/9156251

Pasandi H.B., Nadeem T, 2020. Unboxing MAC protocol design optimization using deep learning. 2020 IEEE International Conference on Pervasive Computing and Communications (PerCom) Workshops, March 2020. https://ieeexplore.ieee.org/document/9156196

Laura Moreno, Gabriele Bavota, Michele Lanza, and  Shepherd DC, 2020. Software documentation: the practitioners' perspective. ACM/IEEE 42nd International Conference on Software Engineering (ICSE '20). Association for Computing Machinery, New York, NY, USA, 590–601. DOI:https://doi.org/10.1145/3377811.3380405 (CORE A* rank)

Anastasia Ruvimova, Junhyeok Kim, Thomas Fritz, Mark Hancock, Shepherd DC, 2020. "Transport Me Away": Fostering Flow in Open Offices through Virtual Reality. 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–14. DOI:https://doi.org/10.1145/3313831.3376724 (CORE A* rank)

Zhang H, Ye C, 2020. DUI-VIO: Depth Uncertainty Incorporated Visual Inertial Odometry based on an RGB-D Camera. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020. http://ras.papercept.net/images/temp/IROS/files/0784.pdf (CORE A rank)

Zhang H, Jin L, Ye C, 2020. The VCU-RVI Benchmark: Evaluating Visual Inertial Odometry for Indoor Navigation Applications with an RGB-D Camera. IEEE/RSJ International Conference on Intelligent Robots and Systems http://ras.papercept.net/images/temp/IROS/files/0685.pdf  (CORE A rank)

L. Jin, H. Zhang, Ye C, 2020. Camera Intrinsic Parameters Estimation by Visual Inertial Odometry for a Mobile Phone with Application to Assisted Navigation. IEEE/ASME International Conference on Advanced Intelligent Mechatronics https://ras.papercept.net/conferences/scripts/rtf/AIM20_ContentListWeb_4.html

Zhang H, Ye C, 2020. A Visual Positioning System for Indoor Blind Navigation. IEEE International Conference on Robotics and Automation https://ieeexplore.ieee.org/document/9196782  (CORE B rank)

Jin L, Zhang H, Ye C, 2020. Human-Robot Interaction for Assisted Object Grasping by a Wearable Robotic Object Manipulation Aid for the Blind. IEEE International Conference on Human-Machine Systems https://ieeexplore.ieee.org/document/9209377

Tuyet Duong, Lei Fan, Jonathan Katz, Phuc Thai, Hong-Sheng Zhou, 2020. 2-hop Blockchain: Combining Proof-of-Work and Proof-of-Stake Securely. ESORICS (2) 2020: 697-712 (CORE A rank) https://link.springer.com/chapter/10.1007%2F978-3-030-59013-0_34

Anne Broadbent, Sevag Gharibian, Hong-Sheng Zhou, 2020. Towards Quantum One-Time Memories from Stateless Hardware. TQC 2020: 6:1-6:25 https://drops.dagstuhl.de/opus/volltexte/2020/12065/

Syed K, Sleeman WC, Nalluri JJ, Kapoor R, Hagan M, Palta J, & Ghosh P, 2020. Artificial intelligence methods in computer-aided diagnostic tools and decision support analytics for clinical informatics. In Artificial Intelligence in Precision Health (pp. 31–59). Elsevier. https://doi.org/10.1016/b978-0-12-817133-2.00002-1

Wu Z, Hu G, Oldfield CJ, Kurgan L, 2020. Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER, In: Kihara D, (Ed.), Methods in Molecular Biology, vol. 2165, pp. 83-101, Springer Nature (ISBN 978-1-0716-0707-7) https://link.springer.com/protocol/10.1007/978-1-0716-0708-4_5

Oldfield CJ, Fan X, Wang, C, Dunker K, Kurgan L, 2020. Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor, In: Kragelund B and Skriver K (Eds), Methods in Molecular Biology, vol. 2141, pp. 21-35, Springer Nature (ISBN 978-1-0716-0523-3) https://link.springer.com/protocol/10.1007/978-1-0716-0524-0_2

Barik A, Kurgan L, 2020. A Comprehensive Overview of Sequence-Based Protein-Binding Residue Predictions for Structured and Disordered Regions, In: Gromiha M, (Ed.), Protein Interactions: Computational Methods, Analysis and Applications, pp. 33-58, World Scientific (ISBN: 978-981-121-187-4) https://www.worldscientific.com/doi/abs/10.1142/9789811211874_0002

Serrano MG, Parikh HI, Brooks JP, Edwards DJ, Arodz T, Edupuganti L, Huang B, Girerd PH, Bokhari YA, Bradley SP, Brooks JL, Dickinson MR, Drake JI, Duckworth RA, Fong SS, Glascock AL, Jean S, Jimenez NR, Khoury J, Koparde VN, Lara AM, Lee V, Matveyev AV, Milton SH, Mistry SD, Rozycki SK, Sheth NU, Smirnova E, Vivadelli SC, Wijesooriya NR, Xu J, Xu P, Chaffin DO, Sexton AL, Gravett MG, Rubens CE, Hendricks-Muñoz KD, Jefferson KK, Strauss JF, Fettweis JM, Buck GA. 2019. Racioethnic diversity in the dynamics of the vaginal microbiome during pregnancy. Nature Medicine 25(6):1001-1011. https://www.nature.com/articles/s41591-019-0465-8 IF: 30.641

Fettweis JM, Serrano MG, Brooks JP, Edwards DJ, Girerd PH, Parikh HI, Huang B, Arodz T, Edupuganti L, Glascock  AL, Xu J, Jimenez NR, Vivadelli SC, Fong SS, Sheth NU, Jean S, Lee V, Bokhari YA, Lara AM, Mistry SD, Duckworth RA, Bradley SP, Koparde VN, Orenda XV, Milton SH, Rozycki SK, Matveyev AV, Wright ML, Huzurbazar SV, Jackson EM, Smirnova E, Korlach J, Tsai YC, Dickinson MR, Brooks JL, Drake JI, Chaffin DO, Sexton AL, Gravett MG, Rubens CE, Wijesooriya NR, Hendricks-Muñoz KD, Jefferson KK, Strauss JF, Buck GA. The vaginal microbiome and preterm birth. Nature Medicine 25(6):1001-1011. https://www.nature.com/articles/s41591-019-0450-2 IF: 30.641

Dhungana A, Arodz T and Bulut E, 2019. Exploiting peer-to-peer wireless energy sharing for mobile charging relief, Ad Hoc Networks 91 (2019): 101882, doi:10.1016/j.adhoc.2019.101882 https://www.sciencedirect.com/science/article/abs/pii/S1570870518305651 IF: 3.49

Dhungana A, Bulut E, 2019. Peer-to-peer energy sharing in mobile networks: Applications, challenges, and open problems, doi: 10.1016/j.adhoc.2019.102029 https://www-sciencedirect-com.proxy.library.vcu.edu/science/article/pii/S1570870519306018 IF: 3.49

Bulut E, Kisacikoglu M, Akkaya K, 2019. Spatio-Temporal Non-intrusive Direct V2V Charge Sharing Coordination, IEEE Transactions on Vehicular Technology (TVT), 68.10 (2019): 9385-9398, doi: 10.1109/TVT.2019.2931954 https://ieeexplore.ieee.org/abstract/document/8782558 IF: 5.33 

Cano A, Krawczyk B, 2019. Kappa Updated Ensemble for Drifting Data Stream Mining. Machine Learning, doi: 10.1007/s10994-019-05840-z https://link.springer.com/article/10.1007/s10994-019-05840-z IF: 2.81

Gonzalez J, Ventura S, Cano A, 2019. Distributed selection of continuous features in multi-label classification using mutual information. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2019.2944298 https://ieeexplore.ieee.org/document/8877992 IF: 11.68

Gonzalez J, Ventura S, Cano A, 2019. Distributed multi-label feature selection using individual mutual information measures. Knowledge-Based Systems, doi: 10.1016/j.knosys.2019.105052 https://www.sciencedirect.com/science/article/abs/pii/S0950705119304459 IF: 5.10

Roseberry M, Krawczyk B, Cano A, 2019. Multi-label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams. ACM Transactions on Knowledge Discovery from Data, 13(6):60 https://dl.acm.org/citation.cfm?doid=3366748.3363573 IF: 2.54

Cano A, Krawczyk B, 2019. Evolving Rule-Based Classifiers with Genetic Programming on GPUs for Drifting Data Streams. Pattern Recognition, 87:248-268 https://www.sciencedirect.com/science/article/abs/pii/S0031320318303765 IF: 5.90

Cano A, Leonard J, 2019. Interpretable Multi-view Early Warning System adapted to Underrepresented Student Populations. IEEE Transactions on Learning Technologies, 12(2):198-211 https://ieeexplore.ieee.org/abstract/document/8691619 IF: 2.32

Djenouri Y, Belhadi A, Lin J, Djenouri D, Cano A, 2019. A Survey on Urban Traffic Anomalies Detection Algorithms. IEEE Access, 7:12192-12205 https://ieeexplore.ieee.org/document/8612931 IF: 4.10

Djenouri Y, Belhadi A, Lin J, Cano A. Adapted k Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow. IEEE Access, 7:10015-10027 https://ieeexplore.ieee.org/document/8613036 IF: 4.10

Skryjomski P, Krawczyk B, Cano A. Speeding up k-Nearest Neighbors Classifier for Large-Scale Multi-Label Learning on GPUs. Neurocomputing, 354:10-19 https://www.sciencedirect.com/science/article/pii/S0925231219304588 IF: 4.07

Nishi MA, Damevski K, 2019. Automatically Identifying Valid API Versions for Software Development Tutorials on the Web. Journal of Software: Evolution and Process, https://onlinelibrary.wiley.com/doi/full/10.1002/smr.2227 IF: 1.30

Chen H, Damevski K, Shepherd DC, Kraft NA, 2019. Modeling Hierarchical Usage Context for Software Exceptions based on Interaction Data. Journal of Automated Software Engineering, https://link.springer.com/article/10.1007/s10515-019-00265-3 IF: 2.20

Chen H, Coogle J, Damevski K, 2019. Modeling Stack Overflow Tags and Topics as a Hierarchy of Concepts. Journal of Systems and Software, https://www.sciencedirect.com/science/article/pii/S0164121219301499 IF: 2.56

Li X, Smith JD, Dinh T, Thai  M. 2019. TipTop: Almost Exact Solutions for Influence Maximization in Billion-Scale Networks. IEEE/ACM Transactions on Networking (TON) 27. https://ieeexplore.ieee.org/document/8661545. IF: 2.19

Nguyen H, Cano A, Tam V, Dinh T, 2019. Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach. IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2019.2904969 https://ieeexplore.ieee.org/document/8666777 IF: 3.86

Jakaria AHM, Rahman MA, Fung C, 2019. A Requirement-Oriented Design of NFV Topology by Formal Synthesis. IEEE Transaction on Network and Service Management. 16(4)  IF: 4.68

Fung C, François J, Cordeiro W, Zhani MF, 2019. Advanced security management. International Journal of Network Management 29(3) IF: 1.23

Fung C, Rashidi B, Motti VG, 2019. Multi-View Permission Risk Notification for Smartphone System. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA). 10(1):42-57. IF: 0.42

Rana, P, Berry, C, Ghosh, P, Fong, SS. Recent advances on constraint-based models by integrating machine learning. Current Opinion in Biotechnology, 64: 85-91, 2020 (eprint ahead of pub). https://www.sciencedirect.com/science/article/pii/S095816691930117X  IF: 8.083

Reddy, D, Ghosh, P, Kumavath, R. Strophanthidin attenuates MAPK, PI3K/AKT/mTOR and Wnt/β-catenin signaling pathways in Human Cancers. Frontiers in Oncology, 2019. https://www.frontiersin.org/articles/10.3389/fonc.2019.01469/abstract  IF: 4.137

Almeida, MO, do Carmo, FLR, Gala-García, A, Kato, R, Gomide, AC, Drummond, RMN, Drumond, MM, Agresti, PM, Barh, D, Brening, B, Ghosh, P, Silva, A, Azevedo, V, Viana, MVC. Lactobacillus crispatus protects against bacterial vaginosis. Genetics and Molecular Research, 18(4), 2019. https://www.geneticsmr.com/articles/lactobacillus-crispatus-protects-against-bacterial-vaginosis  IF: 0.78

Ivanova, ME, Zolnikova, IV, Gorgisheli, KV, Atarshchikov, DS, Ghosh, P and Barh, D. Novel frameshift mutation in NYX gene in a Russian family with complete congenital stationary night blindness. Opthalmic Genetics, 2019. https://www.tandfonline.com/doi/full/10.1080/13816810.2019.1698617  IF: 1.285

Imchen, M, Vennapu, R, Ghosh, P, Kumavath, R. Insights into antagonistic interactions of multidrug resistant bacteria in mangrove sediments from the south Indian state of Kerala. MDPI Microorganims, 7(12): 678, 2019. https://www.mdpi.com/2076-2607/7/12/678  IF: 4.167

Reddy, D, Kumavath, R, Ghosh, P, Barh, D. Lanatoside C induces G2/M cell cycle arrest and suppresses cancer cell growth by attenuating MAPK/Wnt, JAK/STAT, and PI3K/AKT/mTOR signaling pathways. MDPI Biomolecules, 9(12): 792, 2019. https://www.mdpi.com/2218-273X/9/12/792  IF: 4.694

Morais-Rodrigues F, Silv Erio-Machado R, Kato RB, Rodrigues DLN, Valdez-Baez J, Fonseca V, San EJ, Gomes LGR, Dos Santos RG, Vinicius Canário Viana M, da Cruz Ferraz Dutra J, Teixeira Dornelles Parise M, Parise D, Campos FF, de Souza SJ, Ortega JM, Barh D, Ghosh P, Azevedo V, Dos Santos MA. Analysis of the microarray gene expression for breast cancer progression after the application modified logistic regression. Elsevier Gene, 2019. https://www.sciencedirect.com/science/article/abs/pii/S0378111919308273?via%3Dihub  IF: 2.638

Sousa TJ, Parise D, Profeta R, Parise MTD, Gomide ACP, Kato RB, Pereira FL, Figueiredo HCP, Ramos R, Brenig B, Costa da Silva ALD, Ghosh P, Barh D, Góes-Neto A, Azevedo V. Re-sequencing and optical mapping reveals misassemblies and real inversions on Corynebacterium pseudotuberculosis genomes. Nature Scientific Reports, 9(1): 16387, 2019. https://doi.org/10.1038/s41598-019-52695-4   IF: 4.525

Imchen, M, Kumavath, R, Vaz, A, Góes-Neto, A, Barh, D, Ghosh, P, Kozyrovska, N, Podolich, O, and Azevedo, V. 16S rRNA gene amplicon based metagenomic signatures of rhizobiome community in rice field during various growth stages. Frontiers in Microbiology, 10: 2103, 2019. https://www.frontiersin.org/articles/10.3389/fmicb.2019.02103/full   IF: 4.259

Ibraim IC, Parise MTD, Parise D, Sfeir MZT, de Paula Castro TL, Wattam AR, Ghosh P, Barh D, Souza EM, Góes-Neto A, Gomide ACP, Azevedo V.  Transcriptome Profile of Corynebacterium pseudotuberculosis in Response to Iron Limitation. BMC Genomics, 20(1): 663, 2019. https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-6018-1  IF: 4.142

Rana, P, Franco, EF, Rao, Y, Syed, K, Barh, D, Azevedo, V, Ramos, RTJ, Ghosh, P. Evaluation of the genomic basis for Alzheimer’s and Parkinson’s Diseases. Int. J. Mol. Sci., 20:3730, 2019. https://www.mdpi.com/1422-0067/20/15/3730  IF: 4.183

Vilela Rodrigues, T, Jaiswal, A, Ferreira, A, Oliveira, L, Oliveira, CJ, Tiwari, S, Ghosh, P, Benevides, L, Miranda, FM, Azevedo, V, Soares, S. Reverse Vaccinology and Subtractive Genomics reveals new therapeutic targets against Mycoplasma pneumoniae, a causative agent of pneumonia. Royal Society Open Science, 6(7), 2019. https://royalsocietypublishing.org/doi/full/10.1098/rsos.190907   IF: 2.515

Divyashree, M, Mani, MK, Reddy, D, Kumavath, R, Ghosh, P, Azevedo, V, Barh, D. Clinical Applications of Antimicrobial Peptides (AMPs): where do we stand now? Protein & Peptide Letters, 2019. http://www.eurekaselect.com/175117/article   IF: 1.168

Acosta-Smith, E, León-Sicairos, N, Barh, D, Tiwari, S, Flores-villaseñor, HM, Canizalez-Roman, A, Ghosh, P and Azevedo, V. Piper betel compounds Piperidine, Eugenyl acetate, and Chlorogenic acid are broad-spectrum anti-Vibrio compounds that are also effective on MDR strains of the pathogen.  MDPI Pathogens, 8(2): 64, 2019. https://www.mdpi.com/2076-0817/8/2/64 IF: 3.405

Da Silva, WM, Oliveira, LC, Soares, SC, Sousa, CS, Tavares, GC, Resende, CP, Pereira, FL, Ghosh, P, Figueiredo, HCP, Azevedo, V. Quantitative proteomic analysis of the response of probiotic putative Lactocuccus lactis NCDO 2118 strain to different oxygen availability under temperature variation. Frontiers in Microbiology, 2019. https://www.frontiersin.org/articles/10.3389/fmicb.2019.00759/full IF: 4.259

Das, S, Pidaparti, R and Ghosh, P. An integrated parametric model for MT self-assembly formation analysis, Biosystems 176: 6-12, 2019. https://www.sciencedirect.com/science/article/pii/S0303264718302211   IF: 1.623

Tiwari, S, Barh, D, Imchen, M, Rao, E, Kumavath, R, Seenivasan, S, Jaiswal, AK, Jamal, SB, Kumar, V, Ghosh, P, Azevedo, V. Acetate kinase (AcK) is essential for microbial growth and betel compounds potentially target AcK, PhoP, and MDR proteins in M. tuberculosis, V. cholerae, and pathogenic E. coli: An in silico and in vitro study, Curr Top Med Chem. 2019 Jan 20. https://www.ingentaconnect.com/contentone/ben/ctmc/2018/00000018/00000031/art00008  IF: 3.442

Krawczyk B, Koziarski M, Wozniak M, 2019. Radial-based Oversampling for Multiclass Imbalanced Data Classification. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2019.2913673 https://ieeexplore.ieee.org/abstract/document/8743475 IF: 11.68

Cano A, Krawczyk B, 2019. Evolving Rule-Based Classifiers with Genetic Programming on GPUs for Drifting Data Streams. Pattern Recognition, 87:248-268 https://www.sciencedirect.com/science/article/abs/pii/S0031320318303765 IF: 5.90

Gómez-Ríos A, Tabik S, Luengo J, Shihavuddin ASM, Krawczyk B, Herrera F, 2019. Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation. Expert Systems with Applications 118: 315-328 https://www.sciencedirect.com/science/article/pii/S0957417418306523 IF: 4.29

Sáez JA, Galar M, Krawczyk B, 2019. Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy. IEEE Access 7: 83396-83411 https://ieeexplore.ieee.org/document/8746159 IF: 4.10

Koziarski M, Krawczyk B, Wozniak M, 2019. Radial-Based Oversampling for Noisy Imbalanced Data Classification. Neurocomputing 343: 19-33 https://www.sciencedirect.com/science/article/pii/S0925231219301596 IF: 4.07

Skryjomski P, Krawczyk B, Cano A. Speeding up k-Nearest Neighbors Classifier for Large-Scale Multi-Label Learning on GPUs. Neurocomputing, 354:10-19 https://www.sciencedirect.com/science/article/pii/S0925231219304588 IF: 4.07

Cano JR, Gutiérrez PA, Krawczyk B, Wozniak M, García S, 2019. Monotonic Classification: An Overview on Algorithms, Performance Measures and Data Sets. Neurocomputing 341: 168-182 https://www.sciencedirect.com/science/article/pii/S0925231219302383 IF: 4.07

Cano A, Krawczyk B, 2019. Kappa Updated Ensemble for Drifting Data Stream Mining. Machine Learning, doi: 10.1007/s10994-019-05840-z https://link.springer.com/article/10.1007/s10994-019-05840-z IF: 2.81

Roseberry M, Krawczyk B, Cano A, 2019. Multi-label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams. ACM Transactions on Knowledge Discovery from Data, 13(6):60 https://dl.acm.org/citation.cfm?doid=3366748.3363573 IF: 2.54

Krawczyk B, Triguero I, García S, Wozniak M, Herrera F, 2019. Instance Reduction for One-Class Classification. Knowledge and Information Systems 59(3): 601-628 https://link.springer.com/article/10.1007%2Fs10115-018-1220-z IF: 2.40

Yan J, Cheng J, Kurgan L, Uversky VN, 2019. Structural and Functional Analysis of “Non-smelly” Proteins. Cellular and Molecular Life Sciences, doi: 10.1007/s00018-019-03292-1 https://link.springer.com/article/10.1007/s00018-019-03292-1 IF: 7.01

Ghadermarzi S, Li X, Li M, Kurgan L, 2019. Sequence-derived Markers of Drug Targets and Potentially Druggable Human Proteins. Frontiers in Genetics, doi: 10.3389/fgene.2019.01075 https://www.frontiersin.org/articles/10.3389/fgene.2019.01075/full IF: 3.52

Li F, Chen J, Leier A, Marquez-Lago T, Liu Q, Wang Y, Revote J, Smith A, Akutsu T, Webb GI, Kurgan L, Song J, 2019. DeepCleave: A Deep Learning Predictor for Caspase and Matrix Metalloprotease Substrates and Cleavage Sites, Bioinformatics, doi: 10.1093/bioinformatics/btz721 IF: 4.53

Katuwawala A, Oldfield CJ, Kurgan L, 2019. DISOselect: Disorder Predictor Selection at the Protein Level. Protein Science, doi: 10.1002/pro.3756 https://onlinelibrary.wiley.com/doi/full/10.1002/pro.3756 IF: 2.42

Katuwawala A, Oldfield CJ, Kurgan L, 2019. Accuracy of Protein-level Disorder Predictions. Briefings in Bioinformatics, doi: 10.1093/bib/bbz100, IF: 9.10

Oldfield CJ, Peng Z, Uversky VN, Kurgan L, 2019. Codon Selection Reduces GC Content Bias in Nucleic Acids Encoding for Intrinsically Disordered Proteins. Cellular and Molecular Life Sciences, doi: 10.1007/s00018-019-03166-6 https://link.springer.com/article/10.1007%2Fs00018-019-03166-6 IF: 7.01

Amirkhani A, Kolahdoozi M, Wang C, Kurgan L, 2019. Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps. IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi: 10.1109/TCBB.2018.2890261 https://ieeexplore.ieee.org/document/8594649 IF: 2.90

Zhang J, Kurgan L, 2019. SCRIBER: Accurate and Partner Type-specific Prediction of Protein-binding Residues from Proteins Sequences. Bioinformatics, 35(14):i343–i353 IF: 4.53

Zhang F, Song H, Zeng M, Li Y, Kurgan L, Li M, 2019. DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions. Proteomics, 19(12):e1900019 https://onlinelibrary.wiley.com/doi/full/10.1002/pmic.201900019 IF: 3.11

Groenendyk J, Fan Z, Peng Z, Kurgan L, Michalak M, 2019. Endoplasmic Reticulum and the MicroRNA Environment in the Cardiovascular System. Canadian Journal of Physiology and Pharmacology, 97(6):515-527 IF: 2.04

Katuwawala A, Peng Z, Yang J, Kurgan L, 2019. Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions. Computational and Structural Biotechnology Journal, 17:454-46 https://www.sciencedirect.com/science/article/pii/S2001037019300340 IF: 4.72

Brown P, RELISH Consortium (Kurgan L and 1500 other members), Zhou Y, 2019. Large Expert-curated Database for Benchmarking Document Similarity Detection in Biomedical Literature Search. Database, doi: 10.1093/database/baz085 IF: 3.68

Li X, Luo C, Ji H, Zhuang Y, Zhang H, Leung V, 2019. Energy Consumption Optimization for Self-powered IoT Networks with Non-orthogonal Multiple Access. International Journal of Communication Systems. Database, doi: 10.1002/dac.4174, https://onlinelibrary.wiley.com/doi/abs/10.1002/dac.4174 IF: 1.278

Bishnu PB, Paudyal S, Luo Y, Mohanpurkar M, Cheung K, Tonkoski R, Hovsapian R, Myers KS, Zhang R, Zhao P, Manic M, Zhang S, Zhang X. 2019. Big Data Analytics in Smart Grids: State-of-the-Art, Challenges, Opportunities, and Future Directions, IET Smart Grid, vol. 2, no. 2, pp. 141-154. (IF not available)

Marino D, Manic M. 2019. Modeling and Planning under Uncertainty using Deep Neural Networks, IEEE Transactions on Industrial Informatics, vol. 15, no. 8, pp. 4442-4454. https://ieeexplore.ieee.org/document/8717678. IF: 7.37

Damiano A, Rieger C, Vyatkin V, Manic M. 2019. Resilience in Energy Industries—Recent Advances, Open Challenges, and Future Directions, Special Section Editorial, IEEE Transactions on Industrial Informatics, vol. 15, no. 7, pp. 4315-4318. https://ieeexplore.ieee.org/document/8755903. IF: 7.37

Yan X, Ye Y, Qiu X, Manic M, Yu H. 2019. CMIB: Unsupervised Image Object Categorization in Multiple Visual Contexts, IEEE Transactions on Industrial Informatics ( Early Access). https://ieeexplore.ieee.org/document/8823028 IF: 7.37

Wickramasinghe CS, Amarasinghe K, Manic M. 2019. Deep Self-Organizing Maps for Unsupervised Image Classification, IEEE Transactions on Industrial Informatics, vol. 15, no. 11, pp. 5837-5845. https://ieeexplore.ieee.org/document/8669852. IF: 7.37

Henry S, McInnes BT. Indirect association and ranking hypotheses for literature based discovery. BMC bioinformatics. 20 (1), 425, 2019. https://link.springer.com/article/10.1186/s12859-019-2989-9. IF: 2.213.

Henry S, McQuilkin A,  McInnes BT. Association measures for estimating semantic similarity and relatedness between biomedical concepts. Artificial intelligence in medicine, 93, 1-10, 2019. https://www.sciencedirect.com/science/article/pii/S0933365717304475. IF: 3.574

Garousi V, Shepherd DC and Herkiloglu K. Successful Engagement of Practitioners and Software Engineering Researchers: Evidence From 26 International Industry-Academia Collaborative Projects, in IEEE Software, 2019. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8704922&isnumber=5204063. IF:  2.945

Garousi V, Pfahl D, Fernandes J, Felderer M, Mäntylä M, Shepherd DC, Arcuri A, Coşkunçay A, Tekinerdogan B. Characterizing industry-academia collaborations in software engineering: evidence from 101 projects, Empir Software Eng (2019) 24: 2540. https://doi.org/10.1007/s10664-019-09711-y IF: 4.457

Murphy-Hill E, Jaspan C, Sadowski C, Shepherd DC, Phillips M, Winter C, Knight A, Smith E, Jorde M., What Predicts Software Developers' Productivity?, IEEE Transactions on Software Engineering. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8643844&isnumber=4359463 IF: 3.272

Henry RS, Perrin PB, Coston BM, Witten TM. 2019. Transgender and gender non-conforming adult preparedness for aging: Concerns for aging, and familiarity with and engagement in planning behaviors. Int. J.Transgenderism, https://doi.org/10.1080/15532739.2019.1690612 IF 2.325

Seung Geol Choi, Jonathan Katz, Dominique Schröder, Arkady Yerukhimovich, Hong-Sheng Zhou: (Efficient) Universally Composable IF: 1.237

Dana Dachman-Soled, S. Dov Gordon, Feng-Hao Liu, Adam O'Neill, Hong-Sheng Zhou: Leakage Resilience from Program Obfuscation. J. Cryptology 32(3): 742-824 (2019) CORE rank A*; IF: 1.237:

Qasim A, Lopez J, Ahmed I, 2019. Automated Reconstruction of Control Logic for Programmable Logic Controller Forensics. In: Lin Z., Papamanthou C., Polychronakis M. (eds) Information Security. ISC 2019. Lecture Notes in Computer Science, vol 11723. Springer, Cham, DOI:https://doi.org/10.1007/978-3-030-30215-3_20 https://link.springer.com/chapter/10.1007/978-3-030-30215-3_20 (CORE rank B)

Yoo H, Ahmed I, 2019. Control Logic Injection Attacks on Industrial Control Systems. In: Dhillon G., Karlsson F., Hedström K., Zúquete A. (eds) ICT Systems Security and Privacy Protection. SEC 2019. IFIP Advances in Information and Communication Technology, vol 562. Springer, Cham, DOI:https://doi.org/10.1007/978-3-030-22312-0_3 https://link.springer.com/chapter/10.1007/978-3-030-22312-0_3  (CORE rank B)

Yoo H., Kalle S, Smith J, Ahmed I, 2019. Overshadow PLC to Detect Remote Control-Logic Injection Attacks. In: Perdisci R., Maurice C., Giacinto G., Almgren M. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2019. Lecture Notes in Computer Science, vol 11543. Springer, Cham, DOI:https://doi.org/10.1007/978-3-030-22038-9_6 https://link.springer.com/chapter/10.1007/978-3-030-22038-9_6 (CORE rank C)

Kalle S, Ameen N, Yoo H, Ahmed I, 2019. CLIK on PLCs! Attacking control logic with decompilation and virtual PLC. In: Binary Analysis Research (BAR) Workshop, Network and Distributed System Security Symposium (NDSS). 

Deshpande P, Ahmed I, 2019. Topological Scoring of Concept Maps for Cybersecurity Education. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19). ACM, New York, NY, USA, 731-737. DOI: https://doi.org/10.1145/3287324.3287495 https://dl.acm.org/citation.cfm?id=3287495 (CORE rank A)

Deshpande P, Lee C, Ahmed I, 2019. Evaluation of Peer Instruction for Cybersecurity Education. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19). ACM, New York, NY, USA, 720-725. DOI: https://doi.org/10.1145/3287324.3287403 https://dl.acm.org/citation.cfm?id=3287403 (CORE rank A)

Ahmed I, 2019. Ladder Logic Decompiler for Supervisory Control and Data Acquisition (SCADA) Network Forensic. In Proceedings of the 71st Annual Meeting of the American Academy of Forensic Sciences 

Weems C, Richard G, Ahmed I, Russell J, Neill E, Monica M, 2019. Susceptibility and Resilience to Cyber Threat:  Findings from a Scenario Decision Program to Measure Secure and Insecure Computing Behavior. In International Convention of PsychologicalScience (ICPS), March 2019, Paris, France. (Poster)

Dhungana A, Bulut E, 2019. Mobile Energy Balancing in Heterogeneous Opportunistic Networks, in Proceedings of the 16th IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS), Monterey, CA, USA, November 4 - 7. (CORE rank B)

Dhungana A, Bulut E, 2019. Loss-Aware Efficient Energy Balancing in Mobile Opportunistic Networks, in Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 9-13 December 2019, Waikoloa, HI, USA. (CORE rank B)

Yucel F, Bulut E, 2019. Joint Optimization of System and User oriented Task Assignment in Mobile Crowdsensing, in Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 9-13 December 2019, Waikoloa, HI, USA. (CORE rank B)

Hernandez S, Bulut E, 2019. TrinaryMC: Monte Carlo Based Anchorless Relative Positioning for Indoor Positioning, in Proceedings of IEEE Consumer Communications & Networking Conference (CCNC), 10-13 January 2020, Las Vegas, USA. (CORE rank B)

Yucel F, Bulut E, 2019. Location-dependent Task Assignment for Opportunistic Mobile Crowdsensing, in Proceedings of IEEE Consumer Communications & Networking Conference (CCNC), 10-13 January 2020, Las Vegas, USA. (CORE rank B)

Erdin E, Cebe M, Akkaya K, Bulut E, Uluagac S, 2019. A Heuristic-based Private Bitcoin Payment Network Formation Using Off-Chain Links, in Proceedings of The International Conference on Blockchain (Blockchain-2019), Atlanta, July 14-17.

Dhungana A, and Bulut E, 2019. Energy sharing based Content Delivery in Mobile Social Networks, in Proceedings of 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Washington D.C., June (acceptance ratio 16%). https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8793005 (CORE rank A)

Bulut E, Yuksel M, 2019. Integrating In-Network Computing for Secure and Efficient Cascaded Delivery in DTNs, in Proceedings  of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS 2019), Workshop on Network Meets Intelligent Computations (NMIC), Dallas, July. https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8815626 

Chaudhry S, Bulut E, Yuksel M, 2019. A Distributed SDN Application for Cross-Institution Data Access, in Proceedings of 28th International Conference on Computer Communications and Networks (ICCCN 2019), July. https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8846921(CORE rank A)

Ucer E, Buckreus R, Kisacikoglu MC, Bulut E, Guven M, Sozer Y, Giubbolini L, 2019. A Flexible V2V Charger as a New Layer of Vehicle-Grid Integration Framework, in Proceedings of IEEE Transportation Electrification Conference (ITEC). https://ieeexplore.ieee.org/abstract/document/8790483

Bulut E, Guvenc I, Akkaya K, 2019. Privacy Preserving Distributed Matching for Device-to-Device IoT Communications, in Proceedings of The 12th ACM Conference on Security and Privacy (ACM WiSec), Miami, May (Poster).

Chowdhury MU, Maeng SJ, Guvenc I, Bulut E, 2019. Effects of 3D antenna radiation and two-hop relaying on optimal UAV trajectory in cellular networks, in Proceedings of IEEE Aerospace Conference, Big Sky, MT, March. https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8742119

Chowdhury MU, Bulut E, Guvenc I, 2019. Trajectory Optimization in UAV-Assisted Cellular Networks under Mission Duration Constraint, in Proceedings of IEEE Radio & Wireless Week (RWS), Orlando, Jan. https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8714567

Korycki L, Cano A, Krawczyk B, 2019. Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams. IEEE BigData. (acceptance rate 19.7%)

Krawczyk B, Cano A, 2019. Adaptive ensemble active learning for drifting data stream mining. International Joint Conference on Artificial Intelligence, 2763-2771 https://www.ijcai.org/proceedings/2019/0383.pdf (CORE rank A*)

Gonzalez J, Ventura S, Cano A, 2019. ARFF data source library for distributed single/multiple instance, single/multiple output learning on Apache Spark. International Conference on Computational Science, 173-179, https://link.springer.com/chapter/10.1007/978-3-030-22744-9_13 (CORE rank A) 

Moyano J, Gibaja E, Ventura S, Cano A, 2019. Speeding up Classifier Chains in Multi-Label Classification. International Conference on Internet of Things, Big Data and Security, 29-37, http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0007614200290037 

Chatterjee P, Damevski K, Pollock L, Augustine V, Kraft NA, 2019. Exploratory Study of Slack Q&A Chats as a Mining Source for Software Engineering Tools. International Conference on Mining Software Repositories (MSR’19), Montreal, Canada, https://dl.acm.org/citation.cfm?id=3341883.3341961 (CORE rank A) 

Nishi MA, Ciborowska A, Damevski K, 2019. Characterizing Duplicate Code Snippets between Stack Overflow and Tutorials. International Conference on Mining Software Repositories (MSR’19) - Mining Challenge, Montreal, Canada (CORE rank A)

Chen H, Ciborowska A, Damevski K, 2019. Using Automated Prompts for Student Reflection on Computer Security Concepts. ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE’19), Aberdeen, UK, https://dl.acm.org/citation.cfm?id=3319731 (CORE rank A)

Thai PD, Dinh TN. 2018.  Hop-Based Sketch for Large-Scale Influence Analysis. 8th International Conference, (CSoNet'19), HCM City, Vietnam. https://link.springer.com/chapter/10.1007/978-3-030-34980-6_12  

Nguyen LN, Nguyen TDT, Dinh TN,  Thai MT. 2019. OptChain: Optimal Transactions Placement for Scalable Blockchain Sharding. 39thIEEE International Conference on Distributed Computing Systems, Dallas, TX, USA. https://conferences.computer.org/icdcs/2019/pdfs/ICDCS2019-49XpIlu3rRtYi2T0qVYnNX/70i1KKH9y3F9ZUPHt1HHn1/3VWiUa2Mop58ZqsQPv0fQ2.pdf (CORE Rank A)

Bui N, Pham N, Barnitz J, Zou Z, Nguyen P, Truong H, Kim T,  Nguyen A, Farrow N, Xiao J, Deterding R, Dinh T, Vu T, 2019. eBP: A Wearable System For Frequent and Comfortable Blood Pressure Monitoring From User's Ear. The 25th ACM International Conference on Mobile Computing and Networking (MOBICOM'19), Los Carbos, Mexico. (CORE Rank A*) [--- Best Paper Award ---]

Narasareddygari, MR, Walia, GS, Duke, DM, Ramasamy, V, Kiper, J, Davis, DL, ... & Alomari, HW, 2019. Evaluating the Impact of Combination of Engagement Strategies in SEP-CyLE on Improve Student Learning of Programming Concepts. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 1130-1135). ACM. (CORE rank A)

Duke, DM,  Thirunarayanan, M,  Byram, A, & Clarke, PJ, 2019. Students’ Perceptions Of the Implementation of a Cyberlearning Tool Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. https://peer.asee.org/33316

Borchert, O, Byram, A, Duke, DM, Radermacher, AD, Narasareddygari, MR, Walia, GS, 2019. Experiences Using a Cyber Learning Environment in CS1 Classrooms Paper presented at 2019 ASEE Annual Conference & Exposition, Tampa, Florida. https://peer.asee.org/32791

Sosnkowski A, Ramkumar S, Coffman D, Fung C, Levy J. An Analysis of Twitter Users' Political Views using Cross-Account Data Mining. 2nd International Conference on Smart Technologies in Data Science and Communication (SMARTDSC-19).  

Rustgi P, Fung C. DroidNet-An Android Permission Control Recommendation System Based on Crowdsourcing. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM).  https://ieeexplore.ieee.org/abstract/document/8717925 (CORE rank A)

Xu J, Fung C. A Risk-defined Trust Transitivity Model for Group Decisions in Social Networks. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). https://ieeexplore.ieee.org/document/8717900 (CORE rank A)

McCormick B, Halabian H, Fung C. Distributed Orchestration in Cloud Data Centers. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). https://ieeexplore.ieee.org/document/8717916 (CORE rank A)

Xu L, Luan Z, Fung C, Ye D, Qian D. Anomaly Detection Models Based on Context-aware Sequential Long Short-Term Memory Learning. in Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 9-13 December 2019, Waikoloa, HI, USA. (CORE rank B)

Syed, K, Nalluri, J, Sleeman Iv, W, Soni, P, Palta, J, Kapoor, R and Ghosh, P. Treatment Practice Analysis of Intermediate or High Risk Localized Prostate Cancer: A Multi-Center Study with Veterans Health Administration Data. IEEE ICCABS, 2019 (to appear in LNCS proceedings)

Pilkiewicz, KR, Rana, P, Mayo, ML, Ghosh, P. Self-Assembly from a Single-Molecule Perspective, BICT 2019, pp. 147-155. https://link.springer.com/chapter/10.1007/978-3-030-24202-2_11

Franco, E, Maués, D, Alves, R, Guimarães, L, Azevedo, V, Silva, A, Ghosh, P, Morais, J, and Ramos, R. A clustering approach to identify candidates to housekeeping genes based on RNA-seq data. BSB 2019. http://bsb.sbc.org.br/2019/

Nalluri, J, Kapoor, R, Sleeman IV, W, Syed, K, Shahrezaei, MA, Chin, B, Schneider, T, Kim, M, Rana, P, Hagan, M, Ghosh, P and Palta, J. Health Information Gateway and Exchange (HINGE): Automated data aggregation and analytics in Radiation Oncology. ICCR 2019.  (abstract)

Nalluri, J, Kapoor, R, Sleeman IV, W, Syed, K, Shahrezaei, MA, Chin, B, Schneider, T, Kim, M, Rana, P, Hagan, M, Ghosh, P and Palta, J. Infrastructure for a Radiation Oncology Quality Surveillance Program. ICCR 2019. (abstract)

Rana, P, Ghosh, P, Anscher, MS, Mikkelsen, RB, Yakovlev, V. Exosomal miRNA as a non-invasive prediction marker of normal tissue toxicity after radiotherapy for prostate cancer. AACR 2019. (abstract).

Nalluri, J, Kapoor, R, Sleeman IV, W, Syed, K, Shahrezaei, MA, Chin, B, Schneider, T, Kim, M, Rana, P, Hagan, M, Ghosh, P and Palta, J. Health Information Gateway and Exchange (HINGE): Realizing the potential of Big data in Radiation Oncology. ICCR 2019 (abstract)

Syed, K, Sleeman IV, W, Nalluri, J, Hagan, M, Ghosh, P, Palta, J and Kapoor, R. Rule-based pattern matching and text extraction from radiotherapy clinical notes: is there a match? ICCR 2019. (abstract)

Rana, P, Saha, J, Steen, E, Vaidya, A, Rangachari, V, Ghosh, P. A Computational Framework for Preferential Switching of Competing Aβ Aggregation Pathways Based on Game Theory Approach. 2019, Biophysical Journal 116(3):420a, DOI: 10.1016/j.bpj.2018.11.2264. (abstract)

Syed, K, Sleeman IV, W, Nalluri, J, Hagan, M, Ghosh, P, Palta, J and Kapoor, R. Machine Learning Method to Automate Incident Triage in Radiotherapy Incident Reporting and Analysis System (RIRAS), AAPM 2019. (abstract) https://w3.aapm.org/meetings/2019AM/programInfo/programAbs.php?sid=7994&aid=45772

Sleeman IV, W, Nalluri, J, Syed, K, Ghosh, P, Hagan, M, Palta, J and Kapoor, R. Machine Learning Method to Automate Structure Name Mapping, AAPM 2019. (abstract) https://w3.aapm.org/meetings/2019AM/programInfo/programAbs.php?sid=8120&aid=45737 

Nalluri, J, Kapoor, R, Sleeman, WC, Soni, PD, Ghosh, P, Khajamoinuddin, S, Hagan, M, Palta, J. Health Information and Gateway Exchange (HINGE): Big Data Curation Tool for Radiation Oncology. International Journal of Radiation Oncology• Biology• Physics, 2019. (abstract) https://www.redjournal.org/article/S0360-3016(19)33099-8/abstract 

Krawczyk B, Cano A, 2019. Adaptive ensemble active learning for drifting data stream mining. International Joint Conference on Artificial Intelligence, 2763-2771 https://www.ijcai.org/proceedings/2019/0383.pdf (CORE rank A*)

Krawczyk B, Wozniak M, 2019. On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling. International Conference on Computational Sciences ICCS (3): 180-191 https://link.springer.com/chapter/10.1007%2F978-3-030-22744-9_14 (CORE rank A)

Korycki L, Cano A, Krawczyk B, 2019. Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams. IEEE BigData. (acceptance rate 19.7%)

Sleeman IV W, Krawczyk B, 2019. Bagging Using Instance-Level Difficulty for Multi-Class Imbalanced Big Data Classification on Spark. IEEE BigData. (acceptance rate 19.7%)

Korycki L, Krawczyk B, 2019. Unsupervised Drift Detector Ensembles for Data Stream Mining. IEEE International Conference on Data Science and Advanced Analytics DSAA (acceptance rate 24.5%)

Seng S, Li X, Luo C, Ji H, Zhang H, 2019. A D2D-Assisted MEC in the Blockchain-based Framework for UDNs. IEEE International Conference on Communications (ICC’19). https://ieeexplore.ieee.org/abstract/document/8762023  (CORE rank B)

Gao Y, Wang Z, Fang C, Luo C, You S, 2019. Optimal Connected Cruise Control Design with Stochastic Communication Delays. IEEE International Conference on Green Computing and Communications (GreenCom’19). (to appear in IEEE Xplore) 

Ji T, Luo C, Guo Y, Wang Q, Liao W, Li P, 2019. Differentially Private Community Detection in Attributed Social Networks. The 11th Asian Conference on Machine Learning (ACML’19). http://proceedings.mlr.press/v101/ji19a.html (Acceptance Ratio = 30 (oral)/291 = 10.3%)

Chen S, Li X, Luo C, Ji H, Zhang H, 2019. Energy-Efficient Power, Position and Time Control in UAV-assisted Wireless Networks. IEEE Global Telecommunications Conference (GLOBECOM’19), workshop on Intelligent Wireless Emergency Communication Networks.

Han X, Li X, Luo C, Ji H, Zhang H, 2019. Incentive Mechanism with the Caching Strategy for Content Sharing in Vehicular Networks.  IEEE Global Telecommunications Conference (GLOBECOM’19), workshop on V2X Technologies for Next Generation Driving Paradigm.

Marino D, Wickramasinghe C, Rieger C, Manic M. 2019. Data-driven Stochastic Anomaly Detection on Smart-Grid communications using Mixture Poisson Distributions, in Proc. 45th Annual Conference of the IEEE Industrial Electronics Society, IECON 2019, Lisbon, Portugal. https://ieeexplore.ieee.org/abstract/document/8927060 (B1 by Qualis)

Marino D, Wickramasinghe C, Amarasinghe K, Challa H, Richardson P, Jillepalli A, Johnson BK, Rieger C, Manic M. 2019. Cyber and Physical Anomaly Detection in Smart-Grids, in Proc. of the IEEE Resilience Week (RW) 2019, San Antonio, TX, USA. http://www.people.vcu.edu/~mmanic/papers/2019/RW19_MariWickAmarManic_CyberPhysicalADInSmartGrids.pdf (to appear in IEEE Xplore)

Wickramasinghe C, Amarasinghe K, Marino D, Spielman Z, Pray I, Gertman D, and Manic M. 2019. Intelligent Driver System for Improving Fuel Efficiency in Vehicle Fleets, in Proc. 12th International Conference on Human System Interaction, IEEE HSI 2019, Richmond VA, USA.  https://pdfs.semanticscholar.org/80ca/ff62cc9612e0f9fa228888905c9a667ac47a.pdf? (to appear in IEEE Xplore)

Stuart M, Wickramasinghe C, Marino D, Kumbhare D, Holloway K, Manic M. 2019. Machine Learning for Deep Brain Stimulation Efficacy using Dense Array EEG, in Proc. 12th International Conference on Human System Interaction, IEEE HSI 2019, Richmond VA, USA. https://pdfs.semanticscholar.org/d615/47ee1a3e7fc6b7a842dde77671078fb28d23.pdf (to appear in IEEE Xplore)

Wickramasinghe C, Marino D, Yucel F, Bulut E, and Manic M. 2019. Data Driven Hourly Taxi Drop-offs Prediction using TLC Trip Record Data, in Proc. 12th International Conference on Human System Interaction, IEEE HSI 2019, Richmond VA, USA. https://pdfs.semanticscholar.org/24ce/923adc9bcabf4b56d5692995ce233cf408c6.pdf (to appear in IEEE Xplore)

Amarasinghe K, Manic M. 2019. Explaining What a Neural Network has Learned: Toward Explainable Classification, FUZZ-IEEE 2019, New Orleans, USA. https://ieeexplore.ieee.org/document/8858899  (CORE rank A)

Olex A, Maffey L, McInnes BT. NLP Whack-A-Mole: Challenges in Cross-Domain Temporal Expression Extraction. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics, pp. 3682-3692, 2019. CORE rank A.

Lee J, Blake C, McInnes BT. Evaluating ontology coverage and internal structure to better align patients with clinical trials. Proceedings of the Association for Information Science and Technology, 56 (1), 157, 2019.

Henry S, Panahi A, Wijesinghe DS, McInnes BT. A Literature Based Discovery Visualization System with Hierarchical Clustering and Linking Set Associations. AMIA Summits on Translational Science Proceedings, pp. 582, 2019.

Dorn R, Vrana S, and McInnes BT. Improving Accuracy of Patient Speech Transcription Using Dialect-Specific Automatic Speech Recognition Models. In Proceedings of the American Medical Informatics Association Annual Symposium, 2019. (poster)

Olex AL, Gal T, Afshar M, Dligach D, Karnik N, Oakes T, Sharma B, Xie M, McInnes BT, Solway J, Kho A, Cramer WC, and Moeller FG.  Untapped Potential of Clinical Text for Opioid Surveillance.  In Proceedings of the American Medical Informatics Association Annual Symposium, 2019. (poster)

Gurdin G, Vargas JA, Lewinski NA, and McInnes BT.  Quantifying the Sentiment of Online Drug Reviews.  Grace Hopper Celebration of Women in Computing Conference, 2019. (poster)

Cuffy C, Henry S, and McInnes BT. Unsupervised Text Similarity. In Proceedings of the n2c2/OHNLP Shared-Task and Workshop, 2019. (poster)

Shepherd DC, Kraft N, and Francis P, Visualizing the "hidden" variables in robot programs. In Proceedings of the 2nd International Workshop on Robotics Software Engineering (RoSE '19). IEEE Press, Piscataway, NJ, USA, 13-16. DOI: https://doi.org/10.1109/RoSE.2019.00007 (workshop @ ICSE, ICSE is A*)

Ritschel N, Holmes R, Garcia R, and Shepherd DC. Novice-friendly multi-armed robotics programming. In Proceedings of the 2nd International Workshop on Robotics Software Engineering (RoSE '19). IEEE Press, Piscataway, NJ, USA, 29-32. DOI: https://doi.org/10.1109/RoSE.2019.00013 (workshop @ ICSE, ICSE is A*)

Rahimi, F. Jiang, C. Ye, Y. Shen, Dynamic Spatiotemporal Pattern Identification and Analysis Using a Fingertip-Based Electro-Tactile Display Array, IEEE/RSJ International Conference on Intelligent Robots and Systems, Nov. 4-8, 2019. (CORE rank A)

Zhang, L. Jin and C. Ye, A Depth-Enhanced Visual Inertial Odometry for a Robotic Navigation Aid for Blind People, Workshop on Visual-Inertial Navigation: Challenges and Applications at 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. (workshop paper, conference CORE rank A)

Zhang, L. Jin and C. Ye, A Comparative Analysis of Visual-Inertial SLAM for Assisted Wayfinding of the Visually Impaired, in Proc. IEEE Winter Conference on Applications of Computer Vision, pp. 210-217, 2019. (CORE rank A)

Zhang and C. Ye, Wayfinding and Human Intent Detection for Blind Navigation, IEEE International Conference on Human System Interaction, June 25-27, 2019.

Bingsheng Zhang, Hong-Sheng Zhou: Statement Voting. Financial Cryptography 2019: 667-685  (CORE rank B)

Sherman S. M. Chow, Alexander Russell, Qiang Tang, Moti Yung, Yongjun Zhao, Hong-Sheng Zhou: Let a Non-barking Watchdog Bite: Cliptographic Signatures with an Offline Watchdog. Public Key Cryptography (1) 2019: 221-251  (CORE rank B)

Nasr, T. Nadeem, 2019. A Novel Technique for Gait Analysis using Two Waist Mounted Gyroscopes, IEEE Global Communications Conference (GlobeCom), December 9-13, 2019. (CORE rank B)

Pasandi, T. Nadeem, 2019. Collaborative Intelligent Cross-Camera Video Analytics at Edge: Opportunities and Challenges, The International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things (AIChallengeIoT 2019) in conjunction with ACM SenSys, November 10, 2019. https://dl.acm.org/citation.cfm?id=3363360 (SenSys is CORE rank A*)

Uddin, T. Nadeem, S. Nukavarapu, 2019. Extreme SDN Framework for IoT and Mobile Applications Flexible Privacy at the Edge, The 17th IEEE International Conference on Pervasive Computing and Communications (PerCom’19), March 11 - 15, 2019. https://ieeexplore.ieee.org/document/8767413 (CORE rank A*)

H. Pasandi, T. Nadeem. Challenges and Limitations in Automating the Design of MAC Protocols Using Machine-Learning, The 1st IEEE International Conference on Artificial Intelligence in Information and Communication (ICAIIC 2019), February 11-13, 2019. https://ieeexplore.ieee.org/document/8669008

 

Pilkiewicz, K, Rana, P, Mayo, M, Ghosh, P. Molecular Communication and Cellular Signaling from an Information Theory Perspective, Nanoscale Networking and Communications Handbook, CRC Press, 2019. https://www.taylorfrancis.com/books/9780429163043

Katuwawala A, Ghadermarzi S, Kurgan L, 2019. Computational Prediction of Functions of Intrinsically Disordered Regions, In: Uversky VN, (Ed), Dancing protein clouds: Intrinsically disordered proteins in health and disease, Part A, pp. 341-370, Academic Press, (ISBN 978-0-12-816851-6) https://www.sciencedirect.com/science/article/pii/S1877117319300766 

Oldfield C, Peng Z, Kurgan L, 2019. Disordered RNA Binding Region Prediction with DisoRDPbind, In: Heise T, (Ed.), Methods in Molecular Biology, vol. 2106, Springer Nature, (ISBN 978-1-07-160231-7) https://www.springer.com/gp/book/9781071602300 

Oldfield C, Uversky VN, Dunker AK, Kurgan L, 2019. Introduction to Intrinsically Disordered Proteins and Regions, In: Salvi N, (Ed.), Intrinsically Disordered Proteins: Dynamics, Binding and Function, pp. 1-36, Elsevier (ISBN 978-0-12-816348-1) https://www.sciencedirect.com/science/article/pii/B9780128163481000016 

Wang C, Brylinski M, Kurgan L, 2019. PDID: Database of Experimental and Putative Drug Targets in Human Proteome, In: Roy K, (Ed.), In Silico Drug Design: Repurposing Techniques and Methodologies, pp.827-847 Elsevier (ISBN 978-0-12-816125-8) https://www.sciencedirect.com/science/article/pii/B9780128161258000286 

Oldfield C, Chen K, Kurgan L, 2019. Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences, In: Kister A, (Ed.), Methods in Molecular Biology, vol. 1958, pp. 73-100 Springer Nature, (ISBN 978-1-4939-9161-7) https://link.springer.com/protocol/10.1007%2F978-1-4939-9161-7_4 

Salem A, Nadeem T, Salonidis T, Desai N, 2019. Distributed Execution Platforms for Edge Computing, In: Taheri J & Deng S, (Ed.), Edge Computing: Models, Technologies and Applications, The Institution of Engineering and Technology (IET) Books (In Press) https://sites.google.com/site/ietedgebookproposal/home 

Züger M., Meyer A.N., Fritz T., Shepherd DC. (2019) Reducing Interruptions at Work with FlowLight. In: Sadowski C., Zimmermann T. (eds) Rethinking Productivity in Software Engineering. Apress, Berkeley, CA https://link.springer.com/chapter/10.1007/978-1-4842-4221-6_23

Kenney KL, Anderson MO, Pace DP, Yancey NA, Manic M, Amarasinghe K, Marino DL. 2018. Intelligent, adaptive control system and related Methods for integrated processing of biomass, Attorney Docket No. 2939-P13884US (BA‑965), Sep. 2018

Rieger CG, McJunkin TR, Manic M, Amarasinghe K. 2018. Systems and Methods for Control System Security, Attorney Docket No. BA-1009, Nov. 2018

Vollmer T, Rieger C, Manic M, R&D 100 Invention Award, Autonomic Intelligent Cyber Sensor (AICS), awarded during the 56th annual R&D 100 Awards (100 science and technology world innovations in 2018)

Weems C, Ahmed I, Richard III G, Russell J, Neill E. 2018. Susceptibility and Resilience to Cyber Threat: Findings from a Scenario Decision Program to Measure Secure and Insecure Computing Behavior. PLOS ONE. IF: 2.76

Ahmed I, Roussev V. 2018. Peer Instruction Teaching Methodology for Cybersecurity Education. IEEE Security & Privacy. vol. 16 (4). https://ieeexplore.ieee.org/document/8425608 IF: 1.239

Bhatt M, Ahmed I. 2018. Leveraging Relocations in Kernel ELF-binaries for Linux Kernel Version Identification. Digital Investigation Elsevier. https://www.sciencedirect.com/science/article/pii/S1742287618302019 IF: 1.771

Gao X, Petricoin EF, Ward KR, Goldberg SR, Duane TM, Bonchev D, Arodz T, Diegelmann RF. 2018. Network Proteomics of Human Dermal Wound Healing. Physiological Measurement, 39(12):124002 IF: 2.006

Yucel F, Akkaya K, Bulut E. 2018. Efficient and Privacy Preserving Supplier Matching for Electric Vehicle Charging. Elsevier Ad hoc Networks,  doi: 10.1016/j.adhoc.2018.07.029 https://www.sciencedirect.com/science/article/pii/S1570870518305353 IF: 3.151

Yucel F, Bulut E. 2018. Clustered Crowd GPS for Privacy Valuing Active Localization. IEEE Access 6:23213-23221. https://ieeexplore.ieee.org/abstract/document/8347087 IF: 3.557

Binol H, Guvenc I, Bulut E, and Akkaya K. 2018. A hybrid evolutionary search method for complex function optimization problems. IET Electronic Letters. doi: 10.1049/el.2018.6506 https://digital-library.theiet.org/content/journals/10.1049/el.2018.6506 IF: 1.232

Djenouri Y, Djenouri D, Belhadi A, Cano, A. 2018. Exploiting GPU and Cluster Parallelism in Single Scan Frequent Itemset Mining. Information Sciences, doi: 10.1016/j.ins.2018.07.020 https://www.sciencedirect.com/science/article/pii/S0020025518305322 IF: 4.31

Gonzalez-Lopez J, Ventura S, Cano A. 2018. Distributed Nearest Neighbor Classification for Large-Scale Multi-label Data on Spark. Future Generation Computer Systems, 87:66-82 https://www.sciencedirect.com/science/article/pii/S0167739X17327759 IF: 4.64

Melki G, Kecman V, Ventura S, Cano A. 2018. OLLAWV: OnLine Learning Algorithm using Worst-Violators. Applied Soft Computing, 66:384-393 https://www.sciencedirect.com/science/article/pii/S1568494618300991 IF: 3.91

Melki G, Cano A, Ventura S. 2018. MIRSVM: Multi-Instance Support Vector Machine with Bag Representatives. Pattern Recognition, 79:228-241 https://www.sciencedirect.com/science/article/pii/S003132031830061X IF: 3.96

Moyano JM, Gibaja EL, Cios KJ and Ventura S. 2018. An Evolutionary Approach to Build Ensembles of Multi-label Classifiers. Information Fusion,  DOI: 10.1016/j.inffus.2018.11.013 IF: 6.64

Corley C, Damevski K, Kraft N. 2018. Changeset-Based Topic Modeling of Software Repositories. IEEE Transactions on Software Engineering, doi: 10.1109/TSE.2018.2874960 https://ieeexplore.ieee.org/document/8486696 IF: 3.33

Dinh T, Thai M. 2018. AI and Blockchain: A Disruptive Integration. IEEE Computer 51(9): 48-53 https://ieeexplore.ieee.org/document/8481263 IF:1.94

Rashidi B, Fung C, Nguyen A, Vu T, and Bertino E. 2018. Android User Privacy Preserving through Crowdsourcing. IEEE Transaction on Information Forensics & Security (TIFS). https://ieeexplore.ieee.org/abstract/document/8085138 IF: 4.33

Das S, Pidaparti R, and Ghosh P. 2018. An integrated parametric model for MT self-assembly formation analysis. Biosystems, https://www.sciencedirect.com/science/article/pii/S0303264718302211 IF: 1.65.

Parise D, Parise MTD, Viana MVC, Muñoz-Bucio AV, Cortés-Pérez YA, Arellano-Reynoso B, Díaz-Aparicio E, Dorella FA, Pereira FL, Carvalho AF, Figueiredo HCP, Ghosh P, Barh D, Gomide ACP, Azevedo A. 2018. First genome sequencing and comparative analyses of Corynebacterium pseudotuberculosis strains from Mexico. Standards in Genomic Sciences, https://standardsingenomics.biomedcentral.com/articles/10.1186/s40793-018-0325-z IF: 1.6.

Gust K, Chaitankar V, Ghosh P, Wilbank, M, Chen X, Barker N, Pham D, Scanlan L, Rawat A, Talent L, Quinn Jr. M, Vulpe C, Elasri M, Johnson M, Perkins E, McFarland C. 2018. Multiple Environmental Stressors Induce Complex Transcriptomic Responses Indicative of Phenotypic Outcomes in Western Fence Lizard. BMC Genomics, https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-5270-0 IF: 3.73.

Barh D, Tiwari S, Kumavath R, Ghosh P, and Azevedo V. 2018. Linking common non-coding RNAs of human lung cancer and M. tuberculosis. Bioinformation, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137563/ IF: 0.8.

Imchen M, Kumavath R, Barh D, Vaz A, Góes-Neto A, Tiwari S, Ghosh P, Wattam AR, Azevedo V. 2018. Comparative mangrove metagenome reveals the global prevalence of heavy metals and antibiotic resistome across different ecosystems. Scientific Reports, https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-5270-0 IF: 4.12.

Rana P, Pilkiewicz KR, Mayo M, Ghosh P. 2018. Benchmarking the Communication Fidelity of Biomolecular Signaling Cascades Featuring Pseudo-one-dimensional Transport. AIP Advances, https://aip.scitation.org/doi/abs/10.1063/1.5027508 IF: 1.65.

Rangachari V, Dean DN, Rana P, Vaidya A, Ghosh P. 2018. Cause and Consequence of Aβ-Lipid Interactions in Alzheimer disease pathogenesis. Biochimica et Biophysica Acta-Biomembranes, https://www.sciencedirect.com/science/article/pii/S0005273618300841 IF: 3.64.

Hassan SS, Jamal SB, Radusky LG, Tiwari S, Ullah A, Ali J, Behramand, Carvalho P, Shams R, Khan S, Figueiredo H, Barh D, Ghosh P, Silva A, Baunbach J, Röttger R, Gustavo AT and Azevedo V. 2018. The Druggable Pocketome of Corynebacterium diphtheriae: A new approach for in-silico putative druggable targets. Frontiers in Genetics, https://www.frontiersin.org/articles/10.3389/fgene.2018.00044/full IF: 3.8.

Dean DN, Rana P, Campbell RP, Ghosh P and Rangachari V. 2018. Propagation of an Aβ Dodecamer Strain Involves a Three-step Mechanism and a Key Intermediate. Biophysical Journal, https://www.sciencedirect.com/science/article/abs/pii/S0006349517350403 IF: 3.5.

Krawczyk B, Galar M, Wozniak M, Bustince H, Herrera F. 2018. Dynamic ensemble selection for multi-class classification with one-class classifiers. Pattern Recognition, 83: 34-51 https://www.sciencedirect.com/science/article/pii/S0031320318301857 IF: 3.962

Ksieniewicz P, Krawczyk B, Wozniak M. 2018. Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data. Neurocomputing, 271: 28-37 https://www.sciencedirect.com/science/article/pii/S0925231217312195 IF: 3.241

Krawczyk B, Cano A. 2018. Online Ensemble Learning with Abstaining Classifiers for Drifting and Noisy Data Streams. Applied Soft Computing, 68:677-692 https://www.sciencedirect.com/science/article/pii/S1568494617307238 IF: 3.91

Wang C, Kurgan L. 2018. Survey of Similarity-based Prediction of Drug-protein Interactions. Current Medicinal Chemistry, doi: 10.2174/0929867325666181101115314 IF: 3.47

Gao J, Miao Z, Zhang Z, Wei H, Kurgan L. 2018. Prediction of Ion Channels and Their Types from Protein Sequences: Comprehensive Review and Comparative Assessment. Current Drug Targets, doi: 10.2174/1389450119666181022153942 http://www.eurekaselect.com/166525/article IF: 3.11

Groenendyk J, Paskevicius T, Urra H, Viricel C, Wang K, Barakat K, Hetz C, Kurgan L., Agellon LB, Michalak M. 2018. Cyclosporine A Binding to COX-2 Reveals a Novel Signaling Pathway that Activates the IRE1α Unfolded Protein Response Sensor. Scientific Reports, 8:16678 https://www.nature.com/articles/s41598-018-34891-w IF: 4.12

Hu G, Wu Zhonghua, Oldfield C, Wang C, Kurgan L. 2018. Quality Assessment for the Putative Intrinsic Disorder in Proteins. Bioinformatics, IF: 5.48

Hu G, Wang K, Song J, Uversky VN, Kurgan L. 2018. Taxonomic Landscape of the Dark Proteomes: Whole Proteome Scale Interplay between Structural Darkness, Intrinsic Disorder, and Crystallization Propensity. Proteomics, 18(21-22):1800243 https://onlinelibrary.wiley.com/doi/full/10.1002/pmic.201800243 IF: 3.53

Meng F, Kurgan L. 2018. High-throughput Prediction of Disordered Moonlighting Regions in Protein Sequences. Proteins, 86(10):1097-1110 https://onlinelibrary.wiley.com/doi/full/10.1002/prot.25590 IF: 2.27

Wang C, Kurgan L. 2018. Review and Comparative Assessment of Similarity-based methods for Prediction of Drug-protein Interactions in the Druggable Human Proteome. Briefings in Bioinformatics, https://doi.org/10.1093/bib/bby069 IF: 6.30

Chowdhury S, Zhang J, Kurgan L. 2018. In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome. Proteomics, 18(21-22):1800064 https://onlinelibrary.wiley.com/doi/full/10.1002/pmic.201800064 IF: 3.53

Meng F, Murray G, Kurgan L., Donahue HJ. 2018. Functional and Structural Characterization of Osteocytic MLO-Y 4 Cell Proteins that Encode Genes Differentially Expressed in Response to Mechanical Signals in Vitro. Scientific Reports, 8:6716 https://www.nature.com/articles/s41598-018-25113-4 IF: 4.12

Meng F, Chen W, Kurgan L. 2018. fDETECT Webserver: Fast Predictor of Propensity for Protein Production, Purification, and Crystallization. BMC Bioinformatics, 18(1):580 https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1995-z IF: 2.12

Hu G, Wu, Z, Uversky V, Kurgan L. 2018. Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-enriched Interactions. International Journal of Molecular Sciences, 18(12):2761 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751360/ IF: 3.69

Luo C, Yang LT, Min G, and Li P. 2018. Green TCP Transmission over Cognitive Radio Networks, IEEE Transactions on Vehicular Technology (TVT), 67(8):7585-7592, https://ieeexplore.ieee.org/document/8350337/ IF: 4.432

Kumbhare D, Palys V, Toms J, Wickramasinghe C, Amarasinghe K, Manic M, Hughes E, and Holloway KL. 2018. Nucleus Basalis of Meynert Stimulation for Dementia: Theoretical and Technical considerations, Frontiers in Neuroscience, 12:614. DOI: doi: 10.3389/fnins.2018.00614 IF: 3.877

Fernandez Molanes R, Amarasinghe K, Rodriguez-Andina J, and Manic M. 2018. Deep Learning and Reconfigurable Platforms in the Internet of Things: Challenges and Opportunities in Algorithms and Hardware, IEEE Industrial Electronics Magazine, 12(2):36-49, DOI: 10.1109/MIE.2018.2824843 IF: 10.429

Henry S, Cuffy C, McInnes B. 2018. Vector representations of multi-word terms for semantic relatedness. Journal of Biomedical Informatics (JBI) 77:111-19. https://www.sciencedirect.com/science/article/pii/S1532046417302769 IF: 2.88

Henry S, McQuilkin A,  McInnes B. 2018. Association measures for estimating semantic similarity and relatedness between biomedical concepts. Artificial Intelligence in Medicine. In Press. https://www.sciencedirect.com/science/article/pii/S0933365717304475 IF: 2.87

Eakin T, and Witten TM. 2018. Mechanics of population aging and survival. Biogerontology, 19(3-4):251-269, DOI: 10.1007/s10522-018-9755-7 https://link.springer.com/article/10.1007%2Fs10522-018-9755-7 IF:3.702  

Han F, Beleidy SE, Wang H, Ye C, Zhang H. 2018. Learning of Holism-Landmark Graph Embedding for Place Recognition in Long-Term Autonomy. IEEE Robotics and Automation Letters, 3(4): 3669 -3676 https://ieeexplore.ieee.org/document/8411104 IF: not yet published

Li Z, Ma C, Zhou H-S. 2018. Multi-key FHE for multi-bit messages. Sci China Inf Sci, 61(2):029101
https://link.springer.com/article/10.1007%2Fs11432-017-9206-y IF: 2.188

Senthivel S, Dhungana S, Yoo H, Ahmed I, Roussev V. 2018. Denial of Engineering Operations Attacks in Industrial Control Systems. 8th ACM Conference on Data and Application Security and Privacy (CODASPY'18), Tempe, AZ, USA.

Bhatt M, Ahmed I, Lin Z. 2018. Using Virtual Machine Introspection for OS Kernel Security Education. 49th ACM Technical Symposium on Computer Science Education (SIGCSE), Baltimore, Maryland, USA. https://dl.acm.org/citation.cfm?id=3159606 (CORE rank A)

Arodz T, Saeedi S. 2018. Quantum SVM with L1 Regularization. Abstract In: Conference on Quantum Machine Learning Plus, Innsbruck, Austria, September 2018

Dhungana A, Arodz T, Bulut E. 2018. Charging Skip Optimization with Peer-to-Peer Wireless Energy Sharing in Mobile Networks. IEEE International Conference on Communications (ICC). https://ieeexplore.ieee.org/document/8422711 (CORE rank B)

Bulut E, Hernandez S, Dhungana A, and Szymanski BK. 2018. Is Crowdcharging Possible?. IEEE 27th International Conference on Computer Communication and Networks (ICCCN) (pp. 1-9). https://ieeexplore.ieee.org/abstract/document/8487418 (CORE rank A)

Yucel F, Bulut E, Akkaya K. 2018. Privacy Preserving Distributed Stable Matching of Electric Vehicles and Charge Suppliers. Vehicular Technology Conference, Chicago (Core rank B)

Binol H, Bulut E, Akkaya K, Guvenc I. 2018. Time Optimal Multi-UAV Path Planning for Gathering ITS Data from Roadside Units. Vehicular Technology Conference, Chicago (Core rank B)

Bulut E, Guvenc I. 2018. Trajectory optimization for cellular-connected UAVs with disconnectivity constraint. International Conference on Communications (ICC) Workshops pp:1-6. https://ieeexplore-ieee-org.proxy.library.vcu.edu/document/8403623

Bulut E, Guvenc I. 2018. Dynamically Shared Wide-Area Cellular Communication for Hyper-dense IoT Devices. IEEE Conference on Local Computer Networks (LCN) Workshops.

Erdin E, Cebe M, Akkaya K, Solak S, Bulut E, Uluagac S. 2018. Building a Private Bitcoin-based Payment Network among Electric Vehicles and Charging Stations. International Conference on Blockchain (Blockchain-2018), Halifax, Canada.

Cano A, Krawczyk B. 2018. Learning classification rules with differential evolution for high-speed data stream mining on GPUs. IEEE Congress on Evolutionary Computation, pp. 197-204, Rio de Janeiro, Brazil, https://ieeexplore.ieee.org/document/8477961 (CORE rank B; Best Paper Award Nominee)

Roseberry M, Cano A. 2018. Multi-label kNN Classifier with Self Adjusting Memory for Drifting Data Streams. Second International Workshop on Learning with Imbalanced Domains: Theory and Applications (LIDTA@PKDD/ECML), pp. 23-37, Dublin, Ireland, http://proceedings.mlr.press/v94/roseberry18a.html

Ciborowska A, Kraft N, Damevski K. 2018. Detecting and Characterizing Developer Behavior Following Opportunistic Reuse of Code Snippets from the Web. 15th International Conference on Mining Software Repositories (MSR’18), pp. 94-97, Gothenburg, Sweden (CORE rank A, MSR'18 Mining Challenge Winner)

Greco C, Haden T, Damevski K. 2018. StackInTheFlow: Behavior-Driven Recommendation System for Stack Overflow Posts. International Conference on Software Engineering (ICSE 2018) -- Tool Demo Track, pp. 5-8, Gothenburg, Sweden, https://dl.acm.org/citation.cfm?id=3183440.3183477 (CORE rank A*)

Li X, Smith D, Dinh T, Thai M. 2018. Adaptive Crawling with Multiple Bots: A Matroid Intersection Approach. INFOCOM 2018: 1349-1357 (CORE Rank A*) https://ieeexplore.ieee.org/document/8486295

Nguyen H,  Thai M, Dinh T. 2018. Revisiting of 'Revisiting the Stop-and-Stare Algorithms for Influence Maximization. CSoNet 2018: LNCS, 273-285 https://link.springer.com/chapter/10.1007%2F978-3-030-04648-4_23

Nguyen P, Bui N, Nguyen A, Truong H, Suresh A, Whitlock M, Pham D, Dinh T, Vu T. 2018.
TYTH-Typing On Your Teeth: Tongue-Teeth Localization for Human-Computer Interface. MobiSys 2018: 269-282 https://dl.acm.org/citation.cfm?doid=3210240.3210322 (CORE Rank A*)

Truong H, Zhang H, Muncuk U, Nguyen P, Bui N, Nguyen A, Lv Q, Chowdhury K, Dinh T, Vu T. 2018. CapBand: Battery-free Successive Capacitance Sensing Wristband for Hand Gesture Recognition. SenSys 2018: 54-67 https://dl.acm.org/citation.cfm?doid=3274783.3274854 (CORE Rank A*) (Best Paper Award Nominee)

Rashidi B, Fung C, Hamlen KW, Kamisinski A. 2018. HoneyV: A Virtualized Honeynet System Based on Network Softwarization. In IEEE/IFIP Network Operations and Management Symposium (NOMS 2018). Short paper. https://ieeexplore.ieee.org/abstract/document/8406205

Rashidi B, Fung C. 2018. A Scalable and Flexible DDoS Mitigation System Using Network Function Virtualization. In 4TH IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT'18) https://ieeexplore.ieee.org/abstract/document/8406314

Yu H, Fung C, Yang J. 2018. Elastic Network Service Chain with Fine-grained Vertical Scaling. 2018 IEEE Global Communications Conference: Next-Generation Networking and Internet - Next-Generation Networking and Internet. (CORE rank B)

Xu L, Luan Z, Fung C, Wei G, Quian D. 2018. Outlier Detection for Distributed Services using Multi-Frequency Patterns. 14th International Conference on Network and Service Management (CNSM 2018). Short paper.

Abdelzaher A, Ghosh P, Musawi A, Wang J. 2018. Application of Social Network Analytics to Assessing Different Care Coordination Metrics. International Conference on Social Computing and Social Media, pp. 151-160, https://link.springer.com/chapter/10.1007/978-3-319-91485-5_11

Nalluri JJ, Syed K, Rana P, Hudgins P, Ramadan I, Nieporte W, Sleeman IV W, Palta J, Kapoor R, Ghosh P. 2018. A Smart Healthcare Portal for Clinical Decision Making and Precision Medicine. 1st ACM Workshop on Smart and Connected Communities: Technological Foundations, Challenges and Opportunities, SCC-2018, pp. 1-6. https://dl.acm.org/citation.cfm?id=3170530

Nalluri J, Sleeman W, Syed K, Hudgins P, Nieporte W, Ramadan I, Palta J, Hagan M, Ghosh P, Kapoor R. 2018. Health Information Gateway and Exchange (HINGE): Radiation Oncology Data Analytics Portal. 2018. American Association of Physicists in Medicine (Best in Physics Therapy).

Nalluri J, Sleeman W, Syed K, Hudgins P, Nieporte W, Ramadan I, Palta J, Hagan M, Ghosh P, Kapoor R. 2018. HINGE: A demonstration of FHIR framework principles into an integrated health care platform for quality assessment, analytics and smart decision-support apps in Radiation Oncology. 2018. American Association of Physicists in Medicine.

Krawczyk B, Cano A, Wozniak M. 2018. Selecting local ensembles for multi-class imbalanced data classification. International Joint Conference on Neural Networks, pp. 1848-1855, Rio de Janeiro, Brazil, https://ieeexplore.ieee.org/document/8489572 (CORE rank A)

Sharma S, Bellinger C, Krawczyk B, Japkowicz N, Osmar R. Zaïane OR. 2018. Synthetic oversampling with the majority class: A new perspective on handling extreme imbalance. IEEE International Conference on Data Mining (IEEE ICDM 2018), Singapore Nov. 17-20, 2018 (CORE rank A*) (acceptance rate 8.86%)

Korycki L, Krawczyk B. 2018. Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams. IEEE International Conference on Big Data (IEEE BigData'18), Seattle, WA, Dec. 10-13, 2018. (acceptance rate 18.9%)

Mulyar A, Krawczyk B. 2018. Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees. 21st International Conference on Discovery Sciences (DS 2018), pp. 3-17, Limassol, Cyprus, Oct. 29-31, 2018 https://link.springer.com/chapter/10.1007%2F978-3-030-01771-2_1 (acceptance rate 26.9%)

Lapinski A, Krawczyk B, Ksieniewicz P, Wozniak M. 2018. An Empirical Insight Into Concept Drift Detectors Ensemble Strategies. IEEE Congress on Evolutionary Computation, pp. 1-8, Rio de Janeiro, Brazil, https://ieeexplore.ieee.org/document/8477962  (CORE rank B)

Sáez JA, Quintián H, Krawczyk B, Wozniak M, Corchado E. 2018. Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification. 13th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2018), pp. 131-142, Oviedo, Spain, Jun. 20-22, 2018. https://link.springer.com/chapter/10.1007%2F978-3-319-92639-1_12  (CORE rank C)

Chen X, Ji J, Luo C, Liao W, Li P. 2018. Distributed Machine Learning Meets Blockchains: A Decentralized, Secure, and Privacy-preserving Realization, 2018 IEEE International Conference on Big Data (IEEE BigData'18), Seattle, WA, Dec. 10-13, 2018. (acceptance rate 18.9%)

Luo C, Salinas S, Li P. 2018. Efficient Privacy-Preserving Large-scale CP Tensor Decompositions, IEEE Global Communications Conference (GLOBECOM'18), Abu Dhabi, UAE, Dec. 9-13, 2018. (CORE rank B)

Chen X, Ji J, Yu L, Luo C, Li P. 2018. SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud, The 10th Asian Conference on Machine Learning (ACML'18), Beijing, China, Nov. 14-16, 2018.

Amarasinghe K, Manic M. 2018. Improving User Trust on Deep Neural Networks based Intrusion Detection Systems, 44rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2018, Washington DC, USA, Oct. 21-23, 2018. (h-56 by SJR Scimago, B1 by Qualis (grades A1-2, B1-5, C))

Wikramasinghe C, Marino D, Amarasinghe K, Manic M. 2018. Generalization of Deep Learning For Cyber-Physical System Security: A Survey, 44rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2018, Washington DC, USA, Oct. 21-23, 2018. (h-56 by SJR Scimago, B1 by Qualis (possible grades A1-2, B1-5, C))

Marino D, Wikramasinghe C, Manic M. 2018. An Adversarial Approach for Explainable AI in Intrusion Detection Systems, 44rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2018, Washington DC, USA, Oct. 21-23, 2018. (h-56 by SJR Scimago, B1 by Qualis (grades A1-2, B1-5, C))

Amarasinghe K, Wickramasinghe C, Marino D, Rieger C, Manic M. 2018. Framework for Data Driven Health Monitoring of Cyber-Physical Systems, IEEE Resilience Week (RW), Denver, CO, USA, Aug, 20-23, 2018. DOI: 10.1109/RWEEK.2018.8473535

Amarasinghe K, Kenney K, Manic M. 2018. Toward Explainable Deep Neural Network based Anomaly Detection, 11th International Conference on Human System Interaction, IEEE HSI 2018, Gdansk, Poland, July, 04-06, 2018. DOI: 10.1109/RWEEK.2018.8473511

Marino D, Anderson M, Kenney K, Manic M. 2018. Interpretable data-driven modeling in biomass preprocessing, 11th International Conference on Human System Interaction, IEEE HSI 2018, Gdansk, Poland, July, 04-06, 2018. DOI: 10.1109/HSI.2018.8431156 (best paper award)

Wikramasinghe C, Amarasinghe K, Manic M. 2018. Deep Self-Organizing Maps for Visual Data Mining, 11th International Conference on Human System Interaction, IEEE HSI 2018, Gdansk, Poland, July, 04-06, 2018 DOI: 10.1109/HSI.2018.8430845 (best student and young professional paper award)

Mahendran D, Wickramasinghe CS, McInnes B. 2018. SciREL at SemEval-2018 Task 7: A system for semantic relation extraction and classification. 12th international workshop on semantic evaluation (SemEval), pp.853-857.

Olex A, Maffey L, Morgan N, McInnes B. 2018. Chrono at SemEval Task 6: A system for normalizing temporal expressions. 12th international workshop on semantic evaluation (SemEval), pp.97-101.

Alghamdi A, Nadeem T, Cetin M. 2018. BlueMap: A Pervasive Bluetooth-based Vehicle Trajectory Reconstruction System. 37th IEEE Global Communications Conference (Globecom), Abu Dhabi, UAE, (CORE rank B)

Ben Mustafa I, Nadeem T, Halepovic E. 2018. FlexStream: Towards Flexible Adaptive Video Streaming on End Devices using Extreme SDN. 26th ACM International Conference on Multimedia (ACMMM), pp. 555-563, Seoul, Korea, https://dl.acm.org/citation.cfm?id=3240676 (CORE rank A*)

Alasaadi A, Nadeem T, Salem A. 2018. inLaneCom: Enabling In-Lane Vehicular Communication using on-board Smartphones. 15th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS), pp. 134-142 , Chengdu, China, https://ieeexplore.ieee.org/document/8567550 (CORE rank B)

Salem A, Nadeem T. 2018. Blink: Making the case for Bluetooth open source stack. 10th IEEE Wireless Days Conference (WD), pp. 145-150, Dubai, UAE, https://ieeexplore.ieee.org/document/8361710

Zhang H, Jin L, Zhang H, Ye C. 2018. A Comparative Analysis of Visual-Inertial SLAM for Assisted Wayfinding of the Visually Impaired, 2019 IEEE Winter Conference on Applications of Computer Vision (CORE rank A)

Liu X, Zhang H., C. Ye C. 2018. A Wearable Robotic Object Manipulation Aid for the Visually Impaired, 2018 IEEE International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics.

Shen T, Afsar MR, Zhang H., Ye C, Shen X. 2018. Development of a motorized robotic walker guided by a processing system for human walking assistance and rehabilitation, 2018 ASME Dynamic Systems and Control Conference.

Chen Y, Wang Y, Zhou H-S. 2018. Leakage-Resilient Cryptography from Puncturable Primitives and Obfuscation. ASIACRYPT (2) 2018: 575-606 (CORE rank A) https://link.springer.com/chapter/10.1007%2F978-3-030-03329-3_20

Duong T, Chepurnoy A, Fan L, Zhou H-S. 2018. TwinsCoin: A Cryptocurrency via Proof-of-Work and Proof-of-Stake. BCC@AsiaCCS 2018: 1-13

Duong T, Chepurnoy A, Zhou H-S. 2018. Multi-mode Cryptocurrency Systems. BCC@AsiaCCS 2018: 35-46

Russell A, Tang Q, Yung M, Zhou H-S. 2018. Correcting Subverted Random Oracles. CRYPTO (2) 2018: 241-271 (CORE rank A*) https://doi.org/10.1007/978-3-319-96881-0_9

Thai P, Njilla L, Duong T, Fan L, Zhou H-S. 2018. A Generic Paradigm for Blockchain Design. MobiQuitous 2018: 460-469 https://doi.org/10.1145/3286978.3286982 (CORE rank A)

Fernández A, García S, Galar, Prati RC, Krawczyk B, Herrera F. 2018. Learning from Imbalanced Data Sets. Springer, ISBN 978-3-319-98073-7, pp. 1-377 https://link.springer.com/book/10.1007%2F978-3-319-98074-4

Bhatia S, Behal S, Ahmed I. 2018. Distributed Denial of Service Attacks and Defense Mechanism: Current Landscape and Future Directions. In: Advances in Information Security Series, Conti, Somani, and Poovendran (Eds.), Springer. https://link.springer.com/chapter/10.1007/978-3-319-97643-3_3

Ahmed I, Roussev V. 2018. Analysis of Cloud Digital Evidence. In: Security, Privacy, and Digital Forensics in the Cloud, L. Chen, and H. Takabi (Eds.), Wiley.

Bulut E. 2018. Delay Tolerant Mobile Sensor Networks: Routing Challenges and Solutions. In: Ammari H (Ed.),The Philosophy of Mission-Oriented Wireless Sensor Networks , Springer, ISBN 978-3-319-91145-8 doi: 10.1007/978-3-319-91146-5 https://www.springer.com/gp/book/9783319911458

Oldfield C, Uversky VN, Kurgan L. 2018. Predicting Functions of Disordered Proteins with MoRFpred, In: Sikosek T, (Ed.), Methods in Molecular Biology, 1851: 337-352, Humana Press, ISBN 978-1-4939-8736-8 https://link.springer.com/protocol/10.1007/978-1-4939-8736-8_19

Hu G, Kurgan L. 2018. Sequence Similarity Searching, In: Dunn BM, (Ed.), Current Protocols in Protein Science, e71, doi: 10.1002/cpps.71, Wiley, ISBN 978-0-4711-4086-3 https://currentprotocols.onlinelibrary.wiley.com/doi/full/10.1002/cpps.71

Sivils P, Rieger C, Amarasinghe K, Manic M. 2018. Integrated Cyber Physical Assessment and Response for Improved Resiliency, In: Cicirelli F, Guerrieri S, Mastroianni C, Spezzano G, Vinci A (Eds.), The Internet of Things for Smart Urban Ecosystems, Springer, ISBN 978-3-319-96550-5, https://www.springer.com/us/book/9783319965499?gclid=CjwKCAiA0uLgBRABEiwAecFnk8lTKBX06RXQJwjl5_LF7k7U9G2jQe7pfn74wUyFho28QdbJDDqr_xoCthcQAvD_BwE

Bokhari Y, Arodz T. 2017. QuaDMutEx: Quadratic Driver Mutation Explorer. BMC Bioinformatics, vol. 18, article 458 https://doi.org/10.1186/s12859-017-1869-4 IF: 2.45

Cano A. 2017. A Survey on Graphic Processing Unit Computing for Large-Scale Data Mining. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, https://onlinelibrary.wiley.com/doi/full/10.1002/widm.1232 IF: 2.11

Cano A. 2017. An Ensemble Approach to Multi-View Multi-Instance Learning. Knowledge-Based Systems, vol. 136, pp. 46-57, http://www.sciencedirect.com/science/article/pii/S0950705117303799 IF: 4.53

Reyes O, Cano A, Fardoun H, Ventura S. 2017. A Locally Weighted Learning Method Based on a Data Gravitation Model for Multi-Target Regression. International Journal of Computational Intelligence Systems, accepted on Oct 5. IF: 1.57

Cano A, Garcia C, Ventura S. 2017. Extremely High-dimensional Optimization with MapReduce: Scaling Functions and Algorithm. Information Sciences, vol. 415-416, pp. 110-127, http://www.sciencedirect.com/science/article/pii/S0020025517307983 IF: 4.83

Melki G, Cano A, Kecman V, Ventura S. 2017. Multi-Target Support Vector Regression Via Correlation Regressor Chains. Information Sciences, vol. 415-416, pp. 53-69, http://www.sciencedirect.com/science/article/pii/S0020025517307946 IF: 4.83

Cheng W, Yu J, Zhao F, Cheng X. 2017. SSDNet: Small-World Super-Dense Device-to-Device Wireless Networks. IEEE Network, in press, http://ieeexplore.ieee.org/document/8057301/ IF: 7.23

Huang B, Cheng X, Cheng W. 2017. Meet-Cloud for Securely and Accurately Distributing Negative Messages in VANETs. Tsinghua Science and Technology, in press, IF: 1.063

Capurso NN, Song T, Cheng W, Yu J, Cheng X. 2017. An Android-based Mechanism for Energy Efficient Localization depending on Indoor/Outdoor Context. IEEE Internet of Things Journal, vol. 4(2), pp. 299-307, http://ieeexplore.ieee.org/document/7451199/ IF: 7.60

Bryant A, Cios KJ. 2017. SOTXTSTREAM: Density-based Self-Organizing Clustering of Text Streams. PLoS One, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0180543. IF 2.81

Moyano JM, Gibaja EL, Cios KJ and Ventura S. 2017. Review of ensembles of multi-label classifiers: Models, experimental study and prospects. Information Fusion, 44 (2018) 33-45; https://doi.org/10.1016/j.inffus.2017.12.001. IF 5.667

Nishi MA, Damevski K. 2017. Scalable Code Clone Detection and Search based on Adaptive Prefix Filtering. Journal of Systems and Software, https://doi.org/10.1016/j.jss.2017.11.039 IF: 2.44

Damevski K, Chen H, Shepherd DC, Kraft NA, Pollock L. 2017. Predicting Future Developer Behavior in the IDE Using Topic Models. IEEE Transactions on Software Engineering, https://doi.org/10.1109/TSE.2017.2748134 IF: 3.27

Schneider J, Bernstein A, Brocke J, Damevski K, Shepherd DC. 2017. Detecting Plagiarism based on the Creation Process. IEEE Transactions on Learning Technologies, http://dx.doi.org/10.1109/TLT.2017.2720171 IF: 2.26

Naim SM, Damevski K, Hossain MS. 2017. Reconstructing and Evolving Software Architectures Using a Coordinated Clustering Framework. Journal of Automated Software Engineering, vol. 24(3), pp. 543-572 http://dx.doi.org/10.1007/s10515-017-0211-8 IF: 2.62

Nguyen HT, Nguyen TP, Vu TN, Dinh TN. 2017. Outward Influence and Cascade Size Estimation in Billion-scale Networks. Journal Proc. ACM Meas. Anal. Comput. Syst., (presented at SIGMETRICS'17), in press, https://dl.acm.org/citation.cfm?doid=3084457

Nguyen HT, Ghosh P, Mayo ML, Dinh TN. 2017. Social Influence Spectrum at Scale: Near-optimal Solutions for Multiple Budgets at Once. ACM Transactions on Information Systems, vol. 36(2), article 14 https://dl.acm.org/citation.cfm?id=3086700 IF: 2.3

Nalluri J, Rana P, Azevedo V, Barh D, Dinh TN, Vladimirov V, Ghosh P. 2017. Determining Causal miRNAs and Their Signaling Cascade in Diseases Using an Influence Diffusion Model. Scientific Reports, vol. 7(1), article 8133, https://www.nature.com/articles/s41598-017-08125-4 IF: 4.26

Nguyen HT, Thai MT, Dinh TN. 2017. A Billion-scale Approximation Algorithm for Maximizing Benefit in Viral Marketing. IEEE/ACM Transactions on Networking, vol. 25(4), pp. 2419-2429, http://ieeexplore.ieee.org/document/7906620/ IF: 3.4

Nguyen HT, Nguyen N, Vu TN, Hoang HX, Dinh TN. 2017. Transitivity Demolition and the Falls of Social Networks. IEEE Access, vol. 5, pp. 15913-15926, http://ieeexplore.ieee.org/document/7866011/ IF: 3.24

Rashidi B, Fung C, Bertino E. 2017. A Collaborative DDoS Defence Framework using Network Function Virtualization". IEEE Transaction on Information Forensics & Security, vol. 12(10), pp. 2483-2497 http://ieeexplore.ieee.org/document/7934441/ IF: 4.33

Rashidi B, Fung C, Bertino E. 2017. Android Resource Usage Risk Assessment using Hidden Markov Model and Online Learning". Computers and Security, vol. 65, pp. 90-107 http://www.sciencedirect.com/science/article/pii/S0167404816301596 IF: 2.94

Dean DN, Rana P, Campbell RP, Ghosh P, and Rangachari V. 2017. Propagation of an Aβ Dodecamer Strain Involves a Three-step Mechanism and a Key Intermediate. Biophysical Journal, accepted on Nov 28^th 2017; IF: 3.63

Tiwari S, Jamal SB, Hassan SS, Carvalho PVSD, Almeida S, Barh D, Ghosh P, Silva A, Castro TLP, Azevedo V. 2017. Two-Component Signal Transduction Systems of Pathogenic Bacteria as Targets for Antimicrobial Therapy: An Overview. Frontiers in Microbiology, vol. 8, pp. 1878, http://doi.org/10.3389/fmicb.2017.01878 IF: 4.08

Jamal SB, Hassan SS, Tiwari S, Viana MV, Benevides LdJ, Ullah A, Turjanski AJ, Barh D, Ghosh P, Costa DA, Silva A, Rottger R, Baumbach J, Azevedo V. 2017. An Integrative In-Silico Approach for Therapeutic Target Identification in The Human Pathogen Corynebacterium Diphtheriae. PLOS ONE, vol. 12(10), article e0186401. https://doi.org/10.1371/journal.pone.0186401 IF: 2.8

Barh D, García-Solano ME, Tiwari S, Bhattacharya A, Jain N, Torres-Moreno D, Ferri B, Silva A, Azevedo V, Ghosh P, Blum K, Conesa-Zamora P, Perry G. 2017. BARHL1 Is Downregulated in Alzheimer’s Disease and May Regulate Cognitive Functions through ESR1 and Multiple Pathways. Genes, vol. 8(10), article 245, http://www.mdpi.com/2073-4425/8/10/245 IF: 3.6

Nguyen HT, Ghosh P, Mayo ML, Dinh TN. 2017. Social Influence Spectrum at Scale: Near-optimal Solutions for Multiple Budgets at Once. ACM Transactions on Information Systems, vol. 36(2), article 14 https://dl.acm.org/citation.cfm?id=3086700 IF: 2.3

Oliveira A, Oliveira LC, Aburjaile F, Benevides L, Tiwari S, Jamal SB, Silva A, Fugueiredo HCP, Ghosh P, Portela RW, Azevedo V, Wattam AR. 2017. Insight of Genus Corynebacterium: Ascertaining the Role of Pathogenic and Non-pathogenic Species. Frontiers in Microbiology, vol. 8, pp. 1937, http://doi.org/10.3389/fmicb.2017.01937 IF: 4.08

Rana P, Dean DN, Steen ED, Vaidya A, Rangachari V, Ghosh P. 2017. Fatty Acid Concentration and Phase Transitions Modulate Aβ Aggregation Pathways. Scientific Reports, vol. 7(1), article 10370, http://doi.org/10.1038/s41598-017-09794-x IF: 4.26

Imchen M, Kumavath R, Barh D, Avezedo V, Ghosh P, Viana M, Wattam AR. 2017. Searching for Signatures across Microbial Communities: Metagenomic Analysis of Soil Samples from Mangrove and Other Ecosystems. Scientific Reports, vol. 7, article 8859, https://www.nature.com/articles/s41598-017-09254-6 IF: 4.26

Syed K, Abdelzaher A, Mayo M, Ghosh P. 2017. Similar Feed-Forward Loop Crosstalk Patterns may Impact Robust Information Transport across E. coli and S. Cerevisiae Transcriptional Networks, Mobile Networks and Applications, pp. 1-13, https://doi.org/10.1007/s11036-017-0944-4 IF: 3.26

Nguyen HT, Ghosh P, Mayo ML, Dinh TN. 2017. Social Influence Spectrum at Scale: Near-optimal Solutions for Multiple Budgets at Once. ACM Transactions on Information Systems, vol. 36(2), article 14 https://dl.acm.org/citation.cfm?id=3086700 IF: 2.3

Rowland MA, Abdelzaher A, Ghosh P, Mayo ML. 2017. Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks. Biophysical Journal, vol. 112(8), pp. 1539-1550, doi: https://doi.org/10.1016/j.bpj.2017.02.044 IF: 3.63

Oliveira A, Teixeira P, Barh D, Ghosh P, Azevedo V. 2017. Key Amino Acids in Understanding Evolutionary Characterization of Mn/Fe-Superoxide Dismutase: A Phylogenetic and Structural Analysis of Proteins from Corynebacterium and Hosts. Scientific Pages Artif Intell, vol. 1(1), pp. 1-11 https://www.semanticscholar.org/paper/Key-Amino-Acids-in-Understanding-Evolutionary-of-Mn-Oliveira-Teixeira/14afc00876014202f7014dc44e55f6f6d23a6098; IF: not yet published.

Kecman V. 2017. Fast Online Algorithm for Nonlinear Support Vector Machines and Other Alike Models. Optical Memory and Neural Networks, vol. 25(4), pp. 203-218, https://link.springer.com/article/10.3103/S1060992X16040123 IF: 0.71

Melki G, Cano A, Kecman V, Ventura S. 2017. Multi-Target Support Vector Regression Via Correlation Regressor Chains. Information Sciences, vol. 415-416, pp. 53-69, http://www.sciencedirect.com/science/article/pii/S0020025517307946 IF: 4.83

Krawczyk B, Minku LL, Gama J, Stefanowski J, Wozniak M. 2017. Ensemble learning for data stream analysis: A survey. Information Fusion, vol. 37, pp. 132-156 http://www.sciencedirect.com/science/article/pii/S1566253516302329?via%3Dihub IF: 5.67

Krawczyk B, McInnes BT. 2017. Local Ensemble Learning from Imbalanced and Noisy Data for Word Sense Disambiguation. Pattern Recognition, https://doi.org/10.1016/j.patcog.2017.10.028 IF: 4.58

Krawczyk B. 2017. Active and adaptive ensemble learning for online activity recognition from data streams. Knowledge-Based Systems, vol. 138, pp. 69-78 http://www.sciencedirect.com/science/article/pii/S0950705117304513?via%3Dihub IF: 4.53

Ramírez-Gallego S, Krawczyk B, García S, Wozniak M, Benítez JM, Herrera F. 2017. Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark. IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47(10), pp. 2727-2739 http://ieeexplore.ieee.org/document/7993020/ IF: 2.35

Ramírez-Gallego S, Krawczyk B, García S, Wozniak M, Herrera F. 2017. A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing, vol. 239, pp. 39-57 http://www.sciencedirect.com/science/article/pii/S0925231217302631?via%3Dihub IF: 3.32

Kowalski J, Krawczyk B, Wozniak M. 2017. Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble. Engineering Applications of Artificial Intelligence, vol. 57, pp. 134-141 http://www.sciencedirect.com/science/article/pii/S0952197616301981?via%3Dihub IF: 2.89

Krawczyk B, Cyganek B. 2017. Selecting locally specialized classifiers for one-class classification ensembles. Pattern Analysis and Applications, vol. 20(2), pp. 427-439 https://link.springer.com/article/10.1007%2Fs10044-015-0505-z IF: 1.35

Koziarski M, Krawczyk B, Wozniak M. 2017. The deterministic subspace method for constructing classifier ensembles. Pattern Analysis and Applications, vol. 20(4), pp. 981-990 https://link.springer.com/article/10.1007%2Fs10044-017-0655-2 IF: 1.35

Zhang J, Ma Z, Kurgan L. 2017. Comprehensive Review and Empirical Analysis of Hallmarks of DNA, RNA, and Protein Binding Residues in Protein Chains. Briefings in Bioinformatics, accepted on Nov 26. IF: 5.13

Gao J, Wu Z, Hu G, Wang K, Song J, Joachimiak A, Kurgan L. 2017. Survey of Predictors of Propensity for Protein Production and Crystallization with Application to Predict Resolution of Crystal Structures. Current Protein and Peptide Science, http://dx.doi.org/10.2174/1389203718666170921114437 IF: 2.58

Ferreira L, Wu Z, Kurgan L, Uversky VN, Zaslavsky BY. 2017. How to Manipulate Partition Behavior of Proteins in Aqueous Two-phase Systems: Effect of Trimethylamine N-oxide (TMAO). Fluid Phase Equilibria, vol. 449, pp. 217-224 https://www.sciencedirect.com/science/article/pii/S0378381217302637 IF 2.47

Meng F, Uversky VN, Kurgan L. 2017. Comprehensive Review of Methods for Prediction of Intrinsic Disorder and its Molecular Functions. Cellular and Molecular Life Sciences, vol. 74(17), pp. 3069-3090 https://link.springer.com/article/10.1007/s00018-017-2555-4 IF: 5.79

Zhang J, Kurgan L. 2017. Review and Comparative Assessment of Sequence-based Predictors of Protein-binding Residues. Briefings in Bioinformatics, https://doi.org/10.1093/bib/bbx022 IF: 5.13

Yan J, Kurgan L. 2017. DRNApred, Fast Sequence-based Method that Accurately Predicts and Discriminates DNA- and RNA-binding Residues. Nucleic Acids Research, vol. 45(10), pp. e84 https://academic.oup.com/nar/article/45/10/e84/2962183 IF: 10.16

Wang H, Feng L, Webb G, Kurgan L, Song J, Lin D. 2017. Critical Evaluation of Bioinformatics Tools for the Prediction of Protein Crystallization Propensity. Briefings in Bioinformatics, https://doi.org/10.1093/bib/bbx018 IF: 5.13

Valdes Pena MD, Rodriguez-Andina JJ, Manic M. 2017. The Internet of Things: The Role of Reconfigurable Platforms. IEEE Industrial Electronics Magazine, vol. 11(3), pp. 6-19 DOI: 10.1109/MIE.2016.2615575 IF 10.71

Pouri SR, Manic M, Phongikaroon S. 2017. A Novel Framework for Intelligent Signal Detection via Artificial Neural Networks for Cyclic Voltammetry in Pyroprocessing Technology. Annals of Nuclear Energy, vol. 111, pp. 242-254 DOI: 10.1109/MIE.2016.2615575 IF 1.31

Manic M, Amarasinghe K, Rodriguez-Andina JJ, Rieger C. 2016. Intelligent Buildings of the Future: Cyberaware, Deep Learning Powered, and Human Interacting. IEEE Industrial Electronics Magazine, vol. 10(4), pp.32-49 DOI: 10.1109/MIE.2016.2615575 IF 10.71

Krawczyk B, McInnes BT. 2017. Local Ensemble Learning from Imbalanced and Noisy Data for Word Sense Disambiguation. Pattern Recognition, accepted: October 23, 2017 http://www.sciencedirect.com/science/article/pii/S0031320317304351 IF: 4.58

Henry S, McInnes BT. 2017. Literature Based Discovery: Models, Methods and Trends. Journal of Biomedical Informatics, vol. 74, pp. 20-32 http://www.sciencedirect.com/science/article/pii/S1532046417301909 IF: 2.75

Lewinski N, Jimenez I, McInnes BT. 2017. An Annotated Corpus with Nanomedicine and Pharmacokinetic Parameters. Journal of Nanomedicine, vol. 2017(12), pp. 7519-7527 https://www.dovepress.com/an-annotated-corpus-with-nanomedicine-and-pharmacokinetic-parameters-peer-reviewed-article-IJN IF: 4.30

Ye C, Qian X. 2017. 3D Object Recognition of a Robotic Navigation Aid for the Visually Impaired. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. PP(99), DOI: 10.1109/TNSRE.2017.2748419. IF: 3.41

Zhang H, Ye C. 2017. An Indoor Wayfinding System based on Geometric Features Aided Graph SLAM for the Visually Impaired. IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 25(9), pp. 1592-1604. http://ieeexplore.ieee.org/document/7879309/ IF: 3.41

Afsar MR, Wadsworth M, Shen T, Zhang H, Ye C, Shen X. 2017. A Motorized Robotic Walker for Human Walking Assistance. ASME Journal of Medical Devices, accepted for publication. IF: 0.39

Zhang H, Ye C. 2017. RGB-D Camera Based Walking Pattern Recognition by Support Vector Machines for a Smart Rollator. International Journal of Intelligent Robotics and Applications, vol. 1(1), pp. 32-42, 2017. https://link.springer.com/article/10.1007/s41315-016-0002-6 IF: not yet published

Arodz T. 2017. Convolutional Layers based on Directed Multi-Graphs. Proceedings of the Workshop on Learning on Distributions, Functions, Graphs and Groups at Neural Information Processing Systems (NIPS’17) conference, Long Beach, CA. https://nips.cc/Conferences/2017/Schedule?showEvent=8770

Bulut E, Kisacikoglu. M. 2017. Mitigating Range Anxiety via Vehicle-to-Vehicle Social Charging System. Proceedings of the 85th IEEE Vehicular Technology Conference (VTC Spring 2017), pp. 1-5, June 4-7, Sydney, Australia, https://doi.org/10.1109/VTCSpring.2017.8108288 (Core Rank B).

Bulut E, Szymanski B. 2017. Mobile Energy Sharing through Power Buddies. Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2017), pp. 1-6 , March 19-22, San Francisco, https://doi.org/10.1109/WCNC.2017.7925944 (Core Rank B).

Bulut E, Gosain A. 2017. Mobile Core Network Redimensioning for Efficient Resource Utilization. Proceedings of the IEEE International Conference on Computer Communications Workshops (INFOCOM WKSHPS), Performance and Fault Management in Cellular Networks (Perfecto Workshop 2017), pp. 229-234, May 1-4, Atlanta, https://doi.org/10.1109/INFCOMW.2017.8116381.

Dhungana A, Bulut E. 2017. Timely Information Dissemination with Distributed Storage in Delay Tolerant Mobile Sensor Networks. Proceedings of IEEE International Conference on Computer Communications Workshops (INFOCOM WKSHPS), Mission-Oriented Wireless Sensor and Cyber-Physical System Networking (MiseNet Workshop 2017), pp. 103-108, May 1-4, Atlanta, https://doi.org/10.1109/INFCOMW.2017.8116360.

Bulut E, Szymanski B. 2017. Identifying the Space Buddies to Track Lost Items. Proceeding of the 2nd ACM International Workshop on Social Sensing (SocialSens 2017), pp. 69-74, April 21, Pittsburgh, https://doi.org/10.1145/3055601.3055611.

Roberts B, Akkaya K, Bulut E, and Kisacikoglu M. 2017. An Authentication Framework for Electric Vehicle-to-Electric Vehicle Charging Applications. Proceedings of the 14th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS 2017), Research in Networking and Systems (REUNet Workshop), pp. 565-569, October 22-25, Orlando, https://doi.org/10.1109/MASS.2017.93.

Gonzalez-Lopez J, Cano A, Ventura S. 2017. Large-Scale Multi-Label Ensemble Learning on Spark. Proceedings of the 11th IEEE Trustcom/BigDataSE/ICESS, pp. 893-900, Sydney, Australia, http://ieeexplore.ieee.org/document/8029531/ (Core Rank A)

Olex A, McInnes B, Cano A. 2017. Parsing MetaMap Files in Hadoop. Proceedings of the American Medical Informatics Association Symposium

Krawczyk B, McInnes B, Cano A. 2017. Sentiment Classification from Multi-Class Imbalanced Twitter Data Using Binarization. Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol. 10334, pp. 26-37, https://link.springer.com/chapter/10.1007/978-3-319-59650-1_3 (Core Rank C)

Xiao Y, Bai G, Mao J, Liang Z, Cheng W. 2017. Privilege Leakage and Information Stealing through the Android Task Mechanism. Proceedings of the PAC 2017, Aug. 1-3, Washington DC.

Mei B, Cheng X, Cheng W, Cheng X. 2017. Personal Information Prediction Based on Movie Rating Data. Proceedings of the IIKI 2016, Oct. 20-21, Beijing, China.

Coker Z, Damevski K, Le Goues C, Kraft NA, Shepherd DC, Pollock L. 2017. Behavior Metrics for Prioritizing Investigations of Exceptions. Proceedings of the IEEE International Conference on Software Maintenance and Evolution (ICSME 2017), pp. 554-563, Shanghai, China, https://doi.org/10.1109/ICSME.2017.62 (Core Rank A).

Chatterjee P, Nishi MA, Damevski K, Augustine V, Pollock L, Kraft NA. 2017. What Information about Code Snippets Is Available in Different Software-Related Documents? An Exploratory Study. Proceedings of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017), pp. 382-386, Klagenfurt, Austria, https://doi.org/10.1109/SANER.2017.7884638 (Core Rank B)

Nguyen HT, Nguyen TP, Vu TN, Dinh TN. 2017. Outward Influence and Cascade Size Estimation in Billion-scale Networks. Proceedings of the ACM SIGMETRICS Int. Conf. on Measurement and Modeling of Comp. Sys., 2017 (CORE Rank A*)

Bui N, Nguyen A, Nguyen P, Truong H, Ashok A, Dinh TN, Deterding R, Vu T. 2017. PhO2: Optical 3D Printed Elements and NIR/R Light Extraction Techniques for Phone-Base Blood Oxygen Level Measurement, ACM Conf. on Embedded Net. Sensor Systems. Proceedings of the SENSYS’17 (CORE Rank A*; Best Paper Award Nominee, 2nd Price ACM MobiCom 2017 App Contest.)

Nguyen HT, Nguyen PT, Phan H, Dinh TN. 2017. Importance Sketching of Influence Dynamics in Billion-scale Networks. Proceedings of the IEEE International Conference on Data Mining, ICDM’17 (CORE Rank A*)

Bui N, Nguyen A, Nguyen P, Truong H, Ashok A, Dinh TN, Deterding R, Vu T. 2017. Photometry based Blood Oxygen Estimation through Smartphone Cameras. Proceedings of the ACM MobiCom 2017 - S3 Workshop http://mnslab.org/paper/2017%20MobileOx_Nam.pdf (Best Paper Award)

Rashidi B, Fung C, Bertino E. 2017. Android Malicious Application Detection Using Support Vector Machine and Active Learning. Proceedings of the 2017 IEEE/IFIP International Conference on Network and Service Management (CNSM'17). http://www.cnsm-conf.org/2017/detailed-program.html (Core Rank B)

Huang S, Fung C, Zhang S, Wei G, Luan Z, Qian D. 2017. Arena: Adaptive Real-Time Update Anomaly Prediction in Cloud Systems. Proceedings of the 2017 IEEE/IFIP International Conference on Network and Service Management (CNSM'17). http://www.cnsm-conf.org/2017/detailed-program.html (Core Rank B)

Jakaria AHM, Rahman MA, Fung C. 2017. Automated Synthesis of NFV Topology: A Security Requirement-Oriented Design. Proceedings of the 2017 IEEE/IFIP International Conference on Network and Service Management (CNSM'17). (Short paper) http://www.cnsm-conf.org/2017/detailed-program.html

Zhang S, Fung C, Huang S, Luan Z, Qian D. 2017. PSOM: Periodic Self-Organizing Maps for Unsupervised Anomaly Detection in Periodic Time Series. Proceedings of the 2017 IEEE/ACM International Symposium on Quality of Service (IWQoS'17) http://ieeexplore.ieee.org/document/7969174/ (Core Rank B)

Sert SA, Yazici A, Fung C, Roy G. 2017. An Efficient Fuzzy Path Selection Approach to Mitigate Selective Forwarding Attacks in Wireless Sensor Networks. Proceedings of the IEEE International Conference on Fuzzy Systems 2017 (FUZZ-IEEE'17) http://ieeexplore.ieee.org/document/8015552/ (Core Rank A)

Rustgi P, Fung C, Rashidi B, McInnes B. DroidVisor: An Android Secure Application Recommendation System. Proceedings of the 3^rd IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT'17). http://ieeexplore.ieee.org/document/7987440/

Jakaria AHM, Rashidi B, Rahman MA, Fung C, Yang W. 2017. Dynamic DDoS Defense Resource Allocation Using Network Function Virtualization. In ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization (SDN-NFV Security'17). https://dl.acm.org/citation.cfm?id=3041000

Gharibian S, Yirka J. 2017. The Complexity of Estimating Local Physical Quantities. Proceedings of the Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2017), Paris, France.

Roy S, Raj M, Ghosh P, Das SK. 2017. Role of Motifs in Topological Robustness of Bio-inspired Wireless Sensor Networks. Proceedings of the IEEE International Conference on Communications, pp. 1-6 http://ieeexplore.ieee.org/document/7997033/

Syed K, Abdelzaher A, Mayo M, Ghosh P. 2017. Relating Feed-Forward Loop Crosstalk to Robust Information Transport Across Transcriptional Networks. Proceedings of the 10th EAI International Conference on Bio-inspired Information and Communications Technologies, pp. 1-6 http://eudl.eu/doi/10.4108/eai.22-3-2017.152409;

Krawczyk B, Skryjomski P. 2017. Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams. Proceedings of the 27th European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, http://ecmlpkdd2017.ijs.si/papers/paperID592.pdf (CORE Rank A).

Krawczyk B, Wozniak M. 2017. Online query by committee for active learning from drifting data streams. Proceedings of 2017 International Joint Conference on Neural Networks (IJCNN 2017), pp. 2120-2127, Anchorage, AK, USA, http://ieeexplore.ieee.org/document/7966111/ (CORE Rank A).

Koziarski M, Krawczyk B, Wozniak M. 2017. Radial-Based Approach to Imbalanced Data Oversampling. Proceedings of 12th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2017), pp. 318-327, La Rioja, Spain, https://link.springer.com/chapter/10.1007%2F978-3-319-59650-1_27 (CORE Rank C).

Krawczyk B, McInnes B, Cano A. 2017. Sentiment Classification from Multi-Class Imbalanced Twitter Data Using Binarization. Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol. 10334, pp. 26-37, https://link.springer.com/chapter/10.1007/978-3-319-59650-1_3 (Core Rank C)

Skryjomski P, Krawczyk B. 2017. Influence of Minority Class Instance Types on SMOTE Imbalanced Data Oversampling. Proceedings of First International Workshop on Learning with Imbalanced Domains:                Theory and Applications (LIDTA@PKDD/ECML2017), pp. 7-21 Skopje, Macedonia, http://proceedings.mlr.press/v74/skryjomski17a.html

Torgo L, Krawczyk B, Branco P, Moniz N. 2017. Proceedings of Machine Learning Research Volume 74: First International Workshop on Learning with Imbalanced Domains: Theory and Applications http://proceedings.mlr.press/v74/

Wu Z, Hu G, Wang K, Kurgan L. 2017. Exploratory Analysis of Quality Assessment of Putative Intrinsic Disorder in Proteins. Proceedings of the 16th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2017), pp. 722-732, Zakopane, Poland, https://link.springer.com/chapter/10.1007/978-3-319-59063-9_65 (Core Rank C)

Wickramasinghe C, Amarasinghe K, Manic M. 2017. Parallalizable Deep Self-Organizing Maps for Image Classification. Proceedings of the 2017 IEEE Sysposium Series on Computational Intelligence (IEEE SSCI 2017), Honolulu, Hawaii, USA

Stuart M, Manic M. 2017. Survey of Progress in Deep Neural Networks for Resource-Constrained Applications. Proceedings of the 43rd Annual Conference of the IEEE Industrial Electronics Society (IEEE IECON 2017), Beijing, China

Marino D, Amarasinghe K, Anderson M, Yancey N, Nguyen Q, Kenney K, Manic M. 2017. Data Driven Decision Support for Reliable Biomass Feedstock Preprocessing. Proceedings of the 2017 IEEE Symposium on Resilience Week, Wilmington, DE, USA http://ieeexplore.ieee.org/document/8088655/

Carey HJ, Amarasinghe K, Manic M. 2017. Reduction of Massive EEG Datasets for Epilepsy Analysis using Artificial Neural Networks. Proceedings of the 10th International Conference on Human System Interaction (HSI 2017), Ulsan, Republic of Korea http://ieeexplore.ieee.org/document/8005015/ (Best paper award)

Sivils P, Amarasinghe K, Anderson M, Yancey N, Nguyen Q, Kenney K, Manic M. 2017. Dynamic User Interfaces for Control Systems. Proceedings of the 10th International Conference on Human System Interaction (HSI 2017), Ulsan, Korea http://ieeexplore.ieee.org/document/8005045/

Amarasinghe K, Marino D, Manic M. 2017. Deep Learning for Energy Load Forecasting. Proceedings of the International Symposium on Industrial Electronics (IEEE ISIE 2017), Edinburgh, Scotland, June. 19-21, 2017. (B1 Qualis; ; h index 36 by scimago) http://ieeexplore.ieee.org/document/8001465/

Amarasinghe K, Warncke D, Manic M, Wijesinghe DS. 2017. Artificial Neural Networks Based Visual Data Mining for Clinical and Metabolomic Data. Proceedings of the Annual conference of the American Society of Mass Spectrometry (ASMS 2017), Indianapolis, IN

Henry S, Cuffy C, McInnes BT. 2017. Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation. In Proceedings of the 16th Workshop on Biomedical Natural Language Processing (BioNLP) at the Association of Computational Linguistics (ACL), pp. 272-281 http://www.aclweb.org/anthology/W17-2334

McInnes BT, Pedersen T. 2017. Improving Correlation with Human Judgments by Integrating Semantic Similarity with Second--Order Vectors. In Proceedings of the 16th Workshop on Biomedical Natural Language Processing (BioNLP) at the Association of Computational Linguistics (ACL), pp. 107-116 http://aclweb.org/anthology/W17-2313

Rustgi P, Fung C, Rashidi B, McInnes BT. 2017. DroidVisor: An Android Secure Application Recommendation System. In Proceedings of the 3rd IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies (DISSECT), pp. 1071-1076 http://ieeexplore.ieee.org/document/7987440/

Krawczyk B, McInnes BT, Cano A. 2017. Sentiment Classification from Multi-Class Imbalanced Twitter Data Using Binarization. Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, Lecture Notes in Computer Science, vol. 10334, pp. 26-37, https://link.springer.com/chapter/10.1007/978-3-319-59650-1_3 (Core Rank C)

Henry S, McInnes BT. 2017. Semantic Association for Literature Based Discovery. Proceedings of the American Medical Informatics Association https://nlp.cs.vcu.edu/publications/SamHenry_AMIA_2017_abstract.pdf

Olex A, McInnes BT, Cano A. 2017. Parsing MetaMap Files in Hadoop. Proceedings of the American Medical Informatics Association Symposium (Core Rank A)

Salem A, Salonidis T, Desai N, Nadeem T. 2017. Kinaara: Distributed discovery and allocation of mobile edge resources. Proceedings of the 14th IEEE International Conference on Mobile Ad hoc and Sensor Systems (IEEE MASS 2017), pp. 153-161, Orlando, Florida, USA, http://ieeexplore.ieee.org/document/8108739/ (CORE Rank B)

Arab M, Nadeem T. 2017. MagnoPark – Locating On-Street Parking Spaces using Magnetometer-based Pedestrians’ Smartphones. Proceedings of the 14th IEEE International Conference on Sensing, Communication and Networking (SECON), pp. 1-9, San Diego, CA, USA, http://ieeexplore.ieee.org/document/7964915/ (CORE Rank B)

Afsar MR, Wadsworth M, Shen T, Zhang H, Ye C, Shen X. 2017. A Motorized Robotic Walker for Human Walking Assistance. Proceedings of 2017 Design of Medical Devices Conference, pp. V001T05A013

Zhang H, Ye C. 2017. Plane-Aided Visual-Inertial Odometry for Pose Estimation of a 3D Camera based Indoor Blind Navigation. Proceedings of 2017 British Machine Vision Conference.

Qian X, Liu X, Ye C. 2017. A Gaussian-Mixture-Model-based Visual Feature Matching Scheme for Small-Object Detection from RGB-D Data. Proceedings of 2017 IEEE International Conference on Real-time Computing and Robotics, 2017, pp. 91-96.

Zhang H, Ye C. 2017. An Indoor Wayfinding Method for Robotic Navigation Aids. Proceedings of 2017 IEEE International Conference on Robotics and Biomimetics, pp. 467-472.

Russell A, Tang Q, Yung M, Zhou H-S. 2017. Generic Semantic Security against a Kleptographic Adversary. Proceedings of the CCS 2017, pp. 907-922. https://doi.org/10.1145/3133956.3133993 (CORE Rank A*)

Zhang B, Zhou H-S. 2017. Brief Announcement: Statement Voting and Liquid Democracy. Proceedings of the PODC 2017, pp. 359-361. https://doi.org/10.1145/3087801.3087868 (CORE Rank A*)

 

Cios KJ. 2017. Deep Neural Networks – A Brief History. In: Advances in Data Analysis with Computational Intelligence Methods, Gaweda, Kacprzyk, Rutkowski and Yen (Eds.), Studies in Computational Intelligence, Springer, pp. 183-200; also at arXiv preprint: DOI 1701.05549

Nalluri JJ, Azevedo V, Barh D, and Ghosh P. 2017. Bioinformatics and Systems Biology in Bio-engineering. Elsevier Omics Technologies and Bio-engineering: Towards Improving Quality of Life, Elsevier, ISBN: 9780128046593 https://www.elsevier.com/books/omics-technologies-and-bio-engineering-volume-1/barh/978-0-12-804659-3 .

Kamapantula B, Abdelzaher A, Mayo M, Perkins E, Das SK, and Ghosh P. 2017. Quantifying Robustness of Biological Networks Using NS-2. Modeling. Methodologies and Tools for Molecular and Nano-scale Communications, Springer, pp. 273-290 https://link.springer.com/chapter/10.1007/978-3-319-50688-3_12

Meng F, Uversky VN, Kurgan L. 2017. Computational Prediction of Intrinsic Disorder in Proteins, In: Dunn BM, (Ed.), Current Protocols in Protein Science, 88:2.16.1–2.16.14, Wiley, ISBN 978-0-4711-4086-3 https://www.ncbi.nlm.nih.gov/pubmed/28369666

Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Shing Lee W, Taylor D, Hu CW, Long BL, Noren DP, Bisberg AJ; HPN DREAM Consortium: Al-Ouran R, Anton B, Arodz, T Askari Sichani O, Bagheri N, Berlow N, Bohler A, Bonet J, Bonneau R, Budak G, Bunescu R, Caglar M, Cai, B Cai C, Carlon A, Chen L, Ciaccio MF, Cooper G, Creighton CJ, Daneshmand S, de la Fuente A, Di Camillo B, Dutta-Moscato J, Emmett K, Evelo C, Fassia MH, Finkle JD, Finotello F, Gao X, Gao J, Garcia-Garcia J, Ghosh S, Giaretta A, Grosseholz R, Guinney J, Hafemeister C, Hahn O, Haider S, Hase T, Hodgson J, Hoff B, Hao Hsu C, Hu Y, Huang X, Jalili M, Jiang X, Kacprowski T, Kaderali L, Kang M, Kannan V, Kikuchi K, Kim D, H Kitano, Knapp B, Komatsoulis G, Krämer A, Kursa MB, Kutmon M, Li Y, Liang X, Liu Z, Liu Y, Lu S, Lu X, Manfrini M, Matos MRA, Meerzaman D, Min W, Müller CL, Neapolitan RE, Oliva B, Obol Opiyo S, Pal R, Palinkas A, Planas-Iglesias J, Poglayen D, Sambo F, Sanavia T, Sharifi-Zarchi A, Slawek J, Streck A, Strunz S, Tegnér J, Thobe K, Toffolo GM, Trifoglio E, Wan Q, Welch L, Wu JJ, Xue AY, Yamanaka R, Yan C, Zairis S, Zengerling M, Zenil H, Zhang S, Zi Z; Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez-Rodriguez J, Mukherjee S. 2016. Inferring causal molecular networks: empirical assessment through a community-based effort. Nature Methods 13, 310–318, http://www.nature.com/nmeth/journal/v13/n4/full/nmeth.3773.html IF: 25.328

Lu X, Bulut E, Szymanski B. 2016. Towards Limited Scale-free Topology with Dynamic Peer Participation, Computer Networks, vol. 106, pp. 109-121.  IF: 1.44

Capurso NN, Song T, Cheng W, Yu J, Cheng X. 2016. An Android-based Mechanism for Energy Efficient Localization depending on Indoor/Outdoor Context. IEEE Internet of Things Journal, http://ieeexplore.ieee.org/document/7451199/  IF: not yet published

Jing T, Wei X, Cheng W, Guan M, Huo Y, Cheng X. 2016. An Efficient Scheme for Tag Information Update in RFID Systems on Roads. IEEE Transactions on Vehicular Technology, vol. 65(4), pp. 2435-2444 http://ieeexplore.ieee.org/document/7089276/ IF: 2.243

Damevski K, Shepherd D, Schneider J, Pollock L. 2016. Mining Sequences of Developer Interactions in Visual Studio for Usage Smells. IEEE Transactions on Software Engineering. http://dx.doi.org/10.1109/TSE.2016.2592905 IF: 1.5

Ge X, Shepherd D, Damevski K, Murphy-Hill E. 2016. Design and Evaluation of a Multi-Recommendation System for Local Code Search. Journal of Visual Languages and Computing. http://dx.doi.org/10.1016/j.jvlc.2016.07.002 IF: 0.6

Lee J-S, Damevski K, Chen H. 2016. Exploring Computer Science Students’ Learning of Sensor-Driven Mobile App Design: A Case Study. International Journal of Teaching and Case Studies. http://dx.doi.org/10.1504/IJTCS.2016.10001507 IF: not yet published

Luna JM, Cano A, Sakalauskas V, Ventura S. 2016. Discovering Useful Patterns from Multiple Instance Data. Information Sciences, vol. 357, pp. 23-38. http://www.sciencedirect.com/science/article/pii/S0020025516302365 IF 3.36

Cano A, Rojas A. 2016. Cellular automata and applications. UNION, Latin-American Journal of Mathematical Education, vol. 46, pp. 33-48. IF: not yet published

Rashidi B, Fung C, Bertino E. 2016. Android Resource Usage Risk Assessment using Hidden Markov Model and Online Learning. Computers and Security (COSE). http://www.sciencedirect.com/science/article/pii/S0167404816301596 IF: 1.64

Fung C, Zhu Q. 2016. FACID: A Trust-based Collaborative Decision Framework for Intrusion Detection Networks. Ad Hoc Networks Journal (ADHOC).  IF: 1.66

Gharbaouia M, Martini B, Fung C, Paolucci F, Giorgetti A, Castoldi P. 2016. An Incentive-compatible and Trust-aware Multi-Provider Path Computation Element (PCE). Computer Networks (COMNET). http://www.sciencedirect.com/science/article/pii/S1389128616302407 IF: 1.40 

Rashidi B, Fung C, Vu T. 2016. Android Fine-grained Permission Control System with Real-Time Expert Recommendations. Pervasive and Mobile Computing. http://www.sciencedirect.com/science/article/pii/S1574119216300475 IF: 1.70 

Nalluri J, Barh D, Azevedo V, Ghosh P. 2016. miRsig: a consensus-based network inference methodology to identify pan-cancer miRNA-miRNA interaction signatures. Nature Scientific Reports, IF: 5.228

Dean DN, Das PK, Rana P, Burg F, Levites Y, Morgan SE, Ghosh P, Rangachari V. 2016. Strain-specific Fibril Propagation by an Aβ Dodecamer, Nature Scientific Reports, IF: 5.228

Mariano DCB, Pereira FL, Aguiar EL, Oliveira LC, Benevides L, Guimarães L, Folador EL, Sousa TJ, Viana MVS, Ghosh P, Barh D, Figueiredo HCP, Silva A, Ramos RTJ, Azevedo V. 2016. SIMBA: a web tool for managing bacterial genome assembly, BMC Bioinformatics, 17:1344. http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1344-7  IF: 2.435.

Folador EL, Carvalho PVS, Silva WM, Hassan SS, Ferreira RS, Silva A, Baumbach J, Gromiha M, Ghosh P, Barh D, Rottger R, Azevedo V. 2016. In silico protein-protein interactions derive conserved essential proteins in nine strains of Corynebacterium pseudotuberculosis. BMC Systems Biology, 10:103. https://bmcsystbiol.biomedcentral.com/articles/10.1186/s12918-016-0346-4  IF: 2.213.

Saraiva TDL, Etelvino GM, Oliveira M, de Sousa CS, Azevedo MSP, LeBlanc AM, LeBlanc JG, Barh D, Ghosh P, Venanzi F, Figueiredo HCP, Santos RAS, Azevedo V. 2016. Lactococcus lactis NCDO2118 produces anti-hypertensive GABA and exerts acute hypotensive in spontaneously hypertensive rats. Medical Research Archives. http://journals.ke-i.org/index.php/mra/article/view/620 IF: not yet published.

Nalluri J, Barh D, Azevedo V, Ghosh P. 2016. Towards a comprehensive understanding of miRNA regulome and miRNA interaction networks, Journal of Pharmacogenomics and Pharmacoproteomics, 7:160. https://www.omicsonline.org/open-access/towards-a-comprehensive-understanding-of-mirna-regulome-andmirna-interaction-networks-2153-0645-1000160.php?aid=80047  IF: 1.55.

Sousa CS, Barros BL, Barros EG, Barh D, Ghosh P, Azevedo V, Moreira MA. 2016. In silico characterization of genes encoding enzymes 1,2-diacylglycerol cholinephosphotransferase and lysophosphatidylcholine acyltransferase involved in lipid biosynthesis in soybean (Glycine max L. Merril), Genetics and Molecular Research, 15(3). https://www.ncbi.nlm.nih.gov/labs/articles/27706605/  IF: 0.78.

Oliveira A, Teixeira P, Azevedo M, Jamal S, Tiwari S, Almeida S, Barh D, Dorneles E, Haas D, Heinemann M, Ghosh P, Lage A, Ferreira R, Azevedo V. 2016. Corynebacterium pseudotuberculosis may be under anagenesis and biovar equi forms biovar ovis: a phylogenic inference from sequence and structural analysis. BMC Microbiology, 16:100. https://bmcmicrobiol.biomedcentral.com/articles/10.1186/s12866-016-0717-4  IF: 2.58.

Kamapantula B, Mayo M, Perkins E, Ghosh P. 2016. The structural role of the feed forward loop transcriptional motif, Springer Mobile Networks and Applications (MONET), 21(1), pp. 191-205. http://dl.acm.org/citation.cfm?id=2913328  IF: 1.54.

Almeida S, Tiwari S, Mariano D, Souza F, Jamal SB, Coimbra N, Raittz RT, Dorella FA, de Carvalho AF, Pereira FL, de Castro Soares S, Leal CAG, Barh D, Ghosh P, Figueiredo H, Moura-Costa LF, Portela R, Meyer R, Silva A, Azevedo V. 2016. The genome anatomy of Corynebacterium pseudotuberculosis VD57 a highly virulent strain causing Caseous lymphadenitis, Standards in Genomic Sciences, 11(29), pp. 1-8. https://www.ncbi.nlm.nih.gov/pubmed/27066196  IF: 1.594.

Ghosh P, Vaidya A, Rangachari V. 2016. Determination of Critical Nucleation Number for Amyloid-β Aggregation, Mathematical BioSciences, 273, pp. 70-79. https://www.ncbi.nlm.nih.gov/pubmed/26774039  IF: 1.49.

Saez JA, Krawczyk B, Wozniak M. 2016. Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets. Pattern Recognition, vol. 57, pp.  164-178 http://www.sciencedirect.com/science/article/pii/S0031320316001072 IF: 3.399

Zhang Z, Krawczyk B, Garcia S, Rosales-Perez A, Herrera F. 2016. Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data. Knowledge-Based Systems, vol 106, pp. 251-263 http://www.sciencedirect.com/science/article/pii/S0950705116301459 IF: 3.325

Krawczyk B, Wozniak M. 2016. Dynamic classifier selection for one-class classification. Knowledge-Based Systems, vol. 107, pp. 43-53  IF: 3.325

Krawczyk B, Galar M, Jelen L, Herrera F. 2016. Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy. Applied Soft Computing, vol. 38, pp. 714-726  IF 2.857

Krawczyk B, Wozniak M. 2016. Untrained weighted classifier combination with embedded ensemble pruning. Neurocomputing, vol. 196, pp. 14-22  IF: 2.392

Cyganek B, Grana M, Krawczyk B, Kasprzak A, Porwik P, Walkowiak K, Wozniak M. 2016. A Survey of Big Data Issues in Electronic Health Record Analysis. Applied Artificial Intelligence, vol. 30(6), pp. 497-520 http://www.tandfonline.com/doi/abs/10.1080/08839514.2016.1193714?journalCode=uaai20 IF: 0.540

Saez JA, Krawczyk B, Wozniak M. 2016. On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods. Applied Artificial Intelligence, vol. 30(6), pp: 590-609 http://www.tandfonline.com/doi/abs/10.1080/08839514.2016.1193719?journalCode=uaai20 IF: 0.540

Krawczyk B. 2016. Learning from imbalanced data: open challenges and future directions. Progress in Artificial Intelligence, vol. 5(4), pp. 221-232 http://link.springer.com/article/10.1007%2Fs13748-016-0094-0 IF: not yet published

Peng Z, Uversky VN, Kurgan L. 2016. Genes Encoding Intrinsic Disorder in Eukaryota Have High GC Content. Intrinsically Disordered Proteins, http://www.tandfonline.com/doi/full/10.1080/21690707.2016.1262225 IF: not yet published

Lieutaud P, Ferron F, Uversky AV, Kurgan L, Uversky VN, Longhi S. 2016. How Disordered is My Protein and What is Its Disorder For? A Guide through the “Dark Side” of the Protein Universe. Intrinsically Disordered Proteins, accepted on Nov 4. IF: not yet published

Wu Z, Hu G, Wang K, Zaslavsky BY, Kurgan L, Uversky. VN 2016. What are the Structural Features that Drive Partitioning of Proteins in Aqueous Two-phase Systems? BBA Proteins and Proteomics, vol. 1865(1), pp. 113-120  IF: 3.02

Gao J, Cui W, Sheng Y, Jishou J, Kurgan L. 2016. PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types. PLoS ONE, vol. 11(4), article e0152964 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152964 IF: 3.06

Na I, Meng F, Kurgan L, Uversky VN. 2016. Autophagy-related Intrinsically Disordered Proteins in Intra-nuclear Compartments. Molecular BioSystems, vol. 12, pp. 2798-2817 http://pubs.rsc.org/en/content/articlelanding/2016/mb/c6mb00069j IF: 2.83

Meng F, Kurgan L. 2016. DFLpred: High Throughput Prediction of Disordered Flexible Linker Regions in Protein Sequences. Bioinformatics, vol. 32(12), pp. i341-i350 IF: 5.77

Wang C, Uversky VN, Kurgan L. 2016. Disordered Nucleiome: Abundance of Intrinsic Disorder in the DNA- and RNA-binding Proteins in 1121 Species from Eukaryota, Bacteria and Archaea. Proteomics, vol. 16, pp. 1486-1498 http://onlinelibrary.wiley.com/doi/10.1002/pmic.201500177/abstract IF: 4.08

Yan J, Dunker AK, Uversky VN, Kurgan L. 2016. Molecular Recognition Features (MoRFs) in Three Domains of Life. Molecular BioSystems, vol. 12, pp. 697-710 (cover story) http://pubs.rsc.org/en/content/articlelanding/2016/mb/c5mb00640f IF: 2.83

Meng F, Na I, Kurgan L, Uversky VN. 2016. Compartmentalization and Functionality of Nuclear Disorder: Intrinsic Disorder and Protein-Protein Interactions in Intra-Nuclear Compartments. International Journal of Molecular Sciences, vol. 17(1), article 24 http://www.mdpi.com/1422-0067/17/1/24 IF: 3.26

Navarro G, Umberger DK, Manic M. 2016. VD-IT2, Virtual Disk Cloning on Disk Arrays using a Type-2 Fuzzy Controller, IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2016.2633371 IF: 6.701

Manic M, Wijayasekara D, Amarasinghe K, Rodriguez-Andina JJ. 2016. Building Energy Management Systems: The Age of Intelligent and Adaptive Buildings, IEEE Industrial Electronics Magazine, vol. 10(1), pp. 25-39, http://ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber=4154573 IF: 5.30

Bulut E, Szymanski B. 2016. Rethinking Offloading WiFi Access Point Deployment from User Perspective, In Proceedings of IEEE WiMob 2016, Workshop on Smart Environments & Urban Networking, (SEUNet),  New York, NY http://dx.doi.org/10.1109/WiMOB.2016.7763179

Mei B, Cheng X, Cheng W, Cheng X. 2016. Personal Information Prediction Based on Movie Rating Data, In Proceedings of IIKI 2016, Oct. 20-21, Beijing, China.

Jing T, Li J, Huang P, Cheng W, Xing X, Hou Y. 2016. LSKA: Location Similarity Based Key Agreement Scheme for Smartphone Networks, In Proceedings of EUC 2016, Aug 24-26, Paris, France.

Huang B, Jia F, Yu J, Cheng W. 2016. A Transparent Framework Based on Accessing Bridge and Mobile App for Protecting Database Privacy with PKI, In Proceedings of Mobihoc 2016 Workshop PAMCO, July 5-8, Paderborn, Germany. http://dl.acm.org/citation.cfm?id=2940350

Damevski K, Chen H, Shepherd D, Pollock L. 2016. Interactive Exploration of Developer Interaction Traces using a Hidden Markov Model. In Proceedings of the International Conference on Mining Software Repositories (MSR’16), Austin, TX, May, pp. 14-15, 2016, https://doi.org/10.1145/2901739.2901741  (acceptance rate: 27%)

Dinh TN, Thai MT (Eds). 2016. Computing and Combinatorics: Proceedings of 22nd International Conference, COCOON 2016, Ho Chi Minh City, Vietnam, LNCS, Springer, ISBN: 978-3-319-42633-4 http://link.springer.com/book/10.1007%2F978-3-319-42634-1

Cano A, Garcia-Martinez C. 2016. 100 Million Dimensions Large-Scale Global Optimization Using Distributed GPU Computing, In Proceedings of the IEEE World Congress on Computational Intelligence, paper#16334. http://www.people.vcu.edu/~acano/pdf/WCCI_2016.pdf (CORE Rank A).

Padillo F, Luna JM, Cano A, Ventura S. 2016. A Data Structure to Speed-Up Machine Learning Algorithms on Massive Datasets. In Proceedings of the 11th International Conference on Hybrid Artificial Intelligent Systems, LNCS, vol. 9648, pp. 365-376. http://link.springer.com/chapter/10.1007%2F978-3-319-32034-2_31 (CORE Rank C).

Cano A, Garcia-Martinez C. 2016. Optimization of 100 million continuous variables using multiple graphic processing units, In Proceedings of the XI Spanish Conference on Metaheuristics, Evolutionary Algorithms and Bioinspired, pp. 377-386. http://www.people.vcu.edu/~acano/pdf/CAEPIA-2016.pdf

Nguyen HT, Thai MT, Dinh TN. 2016. Cost-aware Targeted Viral Marketing in Billion-scale Networks, In Proceedings of the IEEE Int. Conference on Computer Communications (INFOCOM) http://ieeexplore.ieee.org/document/7524377/ (acceptance rate: 18.3%)

Nguyen HT, Ghosh P, Mayo M, Dinh TN. 2016. Multiple Infection Sources Identification with Provable Guarantees, In Proceedings of the 25th ACM Int. Conf. on Info. and Knowledge Management (CIKM) (acceptance rate: ) http://dl.acm.org/citation.cfm?doid=2983323.2983817 (acceptance rate: 17.6%)

Nguyen HT, Thai MT, Dinh TN. 2016. Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks, In Proceedings of the Annual ACM SIGMOD/PODS Conference (SIGMOD) http://dl.acm.org/citation.cfm?id=2915207 (acceptance rate: 20%)

Li X, Smith JD, Dinh TN, Thai MT. 2016. Privacy Issues in Light of Reconnaissance Attacks with Incomplete Information, In Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI)

Nguyen A, Alqurashi R, Raghebi Z, Banaei-kashani F, Halbower AC, Dinh TN, Vu T. 2016. In-ear Biosignal Recording System: A Wearable For Automatic Whole-night Sleep Staging, In Proceedings of the 14th ACM MobiSys 2016 (MOBISYS), WearSys workshop.

Nguyen HT, Dinh TN. 2016. Targeted Cyber-attacks: Unveiling Target Reconnaissance Strategy via Social Networks, In Proceedings of the IEEE Int. Conf. on Computer Com. (INFOCOM), Security and Privacy in BigData Workshop http://ieeexplore.ieee.org/document/7562088/

Yu H, Yang J, Fung C. 2016. SpongeNet+: A Two-layer Bandwidth Allocation Framework for Cloud Datacenter. In Proceedings of the 18th International Conferences on High Performance Computing and Communications. 2016. (HPCC'16)

Rashidi B, Fung C. 2016. CoFence: A Collaborative DDoS Defence Using Network Function Virtualization. In Proceedings of the 12th International Conference on Network and Service Management. 2016. (CNSM'16) (25% acceptance rate)  http://www.people.vcu.edu/~rashidib/Pub_files/CNSM16/CNSM.pdf

Rashidi B, Fung C. 2016. XDroid: An Android Permission Control Using Hidden Markov Chain and Online Learning. In Proceedings of the IEEE Conference on Communications and Network Security 2016 (CNS'16) (29% acceptance rate)  http://www.people.vcu.edu/~rashidib/Pub_files/CNS16/CNS16.pdf

Rashidi B, Fung C, Nguyen A, Vu T. 2016. Android Permission Recommendation using Transitive Bayesian Inference Model. In Proceedings of the 21st European Symposium on Research in Computer Security 2016 (ESORICS'16) (21% acceptance rate) http://link.springer.com/chapter/10.1007/978-3-319-45744-4_24

Huang S, Fung C, Wang K, Pei P, Luan Z, Qian D. 2016. Using Recurrent Neural Networks Toward Black-Box System Anomaly Prediction, In Proceedings of the IEEE/ACM International Symposium on Quality of Service 2016 (IWQoS'16) (20% acceptance rate)  http://ieeexplore.ieee.org/abstract/document/7590435/

Jakaria AHM, Yang W, Rashidi B, Fung C, Rahman M. 2016. VFence: A Defense against Distributed Denial of Service Attacks using Network Function Virtualization, In Proceedings of the 11th IEEE International Workshop on Security, Trust, and Privacy for Software Applications (STPSA 2016). (32.5% acceptance rate) http://ieeexplore.ieee.org/abstract/document/7552250/

Yang W, Fung C. 2016. A survey on security in network functions virtualization, In Proceedings of the IEEE Conference on Network Softwarization (Netsoft'16). Seoul, Korea. Short paper. (37% acceptance rate) http://people.vcu.edu/~cfung/research/NetSoft2016.pdf

Rashidi B, Fung C. 2016. BotTracer: Bot User Detection Using Clustering Method in RecDroid. In In Proceedings of the IEEE/IFIP Workshop on Security for Emerging Distributed Network Technologies 2016 (DISSECT'16). Istanbul, Turkey. (40% acceptance rate) http://ieeexplore.ieee.org/document/7502994/?arnumber=7502994&tag=1

de Beaudrap N, Gharibian S. 2016. A linear time algorithm for quantum 2-SAT, In Proceedings of the 31st Conference on Computational Complexity (CCC), volume 50 of Leibniz International Proceedings in Informatics (LIPIcs), pp. 27:1-27:21 http://drops.dagstuhl.de/opus/volltexte/2016/5836/.

Nazi A, Raj M, di Francesco M, Ghosh P, Das SK. 2016. Efficient Communications in Wireless Sensor Networks Based on Biological Robustness, IEEE DCOSS 2016, pp. 161-168, http://ieeexplore.ieee.org/document/7536333/ (acceptance rate: 37%).

Kecman V, Melki G. 2016. Fast Online Algorithms for Support Vector Machines, In Proceedings of the of IEEE SE Conf, Norfolk, VA

Melki G, Kecman V. 2016. Speeding Up Online Training of L1 Support Vector Machines, In Proceedings of the of IEEE SE Conf, Norfolk, VA

Kecman V. 2016. Fast online algorithm for nonlinear support vector machines and other alike models, Invited Lecture, Lekcii po Neuroinformatike, Neuroinformatics 2016, ISBN 978-5-7262-2241-7, NRNU MEPhI, Moscow

Krawczyk B. 2016. Cost-sensitive one-vs-one ensemble for multi-class imbalanced data. In Proceedings of 2016 International Joint Conference on Neural Networks (IJCNN 2016), pp. 2447-2452 http://ieeexplore.ieee.org/document/7727503/ (CORE rank A)

Krawczyk B, Saez JA, Wozniak M. 2016. Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines. In Proceedings of 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), pp. 915-922 http://ieeexplore.ieee.org/document/7737786/ (CORE rank A)

Krawczyk B. 2016. GPU-Accelerated Extreme Learning Machines for Imbalanced Data Streams with Concept Drift. In Proceedings of International Conference on Computational Science 2016 (ICCS 2016), pp. 1692-1701 http://www.sciencedirect.com/science/article/pii/S1877050916309966 (CORE rank A)

Krawczyk B. 2016. Hybrid One-Class Ensemble for High-Dimensional Data Classification. In Proceedings of 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016), vol 2, pp. 136-144 http://link.springer.com/chapter/10.1007%2F978-3-662-49390-8_13

Koziarski M, Krawczyk B, Wozniak M. 2016. Forming Classifier Ensembles with Deterministic Feature Subspaces. In Proceedings of 2016 Federated Conference on Computer Science and Information Systems (FedCSIS 2016), pp. 89-95 https://fedcsis.org/proceedings/2016/drp/552.html

Marino D, Amarasinghe K, Manic M. 2016. Simultaneous Generation-Classification Using LSTM, In Proceedings of 2016 IEEE Symposium Series on Computational Intelligence IEEE SSCI 2016, Athens, Greece, Dec. 6-9, 2016. http://ssci2016.cs.surrey.ac.uk/

Pouri SR, Wijayasekara D, Manic M, Phongikaroon S. 2016. Development of a Smart Signal Detection Method for Cyclic Voltammetry via Artificial Neural Intelligence, In Proceedings of 2016 American Nuclear Society Winter Meeting and Expo, Las Vegas, NV, Nov. 6-10, 2016. http://www.ans.org/meetings/m_147

Marino D, Amarasinghe K, Manic M. 2016. Building Energy Load Forecasting using Deep Neural Networks, In Proceedings of 42nd Annual Conference of the IEEE Industrial Electronics Society, IEEE IECON 2016, Florence, Italy, Oct. 24-27, 2016. http://ieeexplore.ieee.org

Carey H, Manic M. 2016. Epileptic Spike Detection with EEG using Artificial Neural Networks, In Proceedings of IEEE 9th International Conference on Human System Interaction, IEEE HSI 2016, Portsmouth, England, July 6-8, 2016. DOI: 10.1109/HSI.2016.7529614.

Amarasinghe K, Sivils P, Manic M. 2016. EEG Feature Selection for Thought Driven Robots using Evolutionary Algorithms," In Proceedings of IEEE 9th International Conference on Human System Interaction, IEEE HSI 2016, Portsmouth, England, July 6-8, 2016. DOI: 10.1109/HSI.2016.7529657

Ostrom LT, Verner KM, Manic M, Amarasinghe K, Wijayasekara D. 2016. Multi-Use High-Technology Testbed, In Proceedings of IEEE 9th International Conference on Human System Interaction, IEEE HSI 2016, Portsmouth, England, July 6-8, 2016.  DOI: 10.1109/HSI.2016.7529646

Carey H, Manic M. 2016. HTML Web Content Extraction Using Paragraph Tags, In Proceedings of 25th International Symposium on Industrial Electronics, IEEE ISIE 2016, Santa Clara, USA, June 8-10, 2016.  DOI: 10.1109/ISIE.2016.7745047

Marino D, Manic M. 2016. Fast Trajectory Simplification Algorithm for Natural User Interfaces in Robot Programming by Demonstration, In Proceedings of 25th International Symposium on Industrial Electronics, IEEE ISIE 2016, Santa Clara, USA, June 8-10, 2016. DOI: 10.1109/ISIE.2016.7745011

McInnes BT, Murphy R, Jones G, Hodson M, Izadi T, Jimenez I, Lewinski N. 2016. Nanomedicine Entity Extraction. American Medical Informatics Symposium (AMIA).

Lewinski N, Hodson M, Izadi T, Jimenez I, Murphy R, Jones G, McInnes BT. 2016. END, an Annotated Nanomedicine Corpus. International Nanotoxicology Congress (nanoTOX).

McInnes BT. 2016. VCU at Semeval-2016 Task 14: Evaluating Similarity Measures for Semantic Taxonomy Enrichment. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval).

Briones G, Amarasinghe K, McInnes BT. 2016. VCU-TSA at Semeval-2016 Task 4: Sentiment Analysis in Twitter. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval), June 2016.

Korcovelos E, Pakhomov SV, McInnes BT. 2016. Automated Linguistic Analysis of Patients with Dementia and Mild Cognitive Impairment. In Proceedings of the Alzheimer’s Association International Conference (AAIC).

Russell A, Tang Q, Yung M, Zhou H-S. 2016. Cliptography: Clipping the Power of Kleptographic Attacks. In Proceedings of ASIACRYPT (2) 2016, pp. 34-64.

Kiayias A, Zhou H-S, Zikas V. 2016. Fair and Robust Multi-party Computation Using a Global Transaction Ledger. In Proceedings of EUROCRYPT (2) 2016, pp. 705-734

Chen Y-C, Chow S, Chung K-M, Lai R, Lin W-K, Zhou H-S. 2016. Cryptography for Parallel RAM from Indistinguishability Obfuscation. In Proceedings of ITCS 2016, pp. 179-190

Dachman-Soled D, Gordon SD, Liu F-H, O'Neill A, Zhou H-S. 2016. Leakage-Resilient Public-Key Encryption from Obfuscation. In Proceedings of Public Key Cryptography (2) 2016, pp. 101-128

Green MD, Katz J, Malozemoff AJ, Zhou H-S. 2016. A Unified Approach to Idealized Model Separations via Indistinguishability Obfuscation. In Proceedings of SCN 2016, pp. 587-603

Blocki J, Zhou H-S. 2016. Designing Proof of Human-Work Puzzles for Cryptocurrency and Beyond. In Proceedings of TCC (B2) 2016, pp. 517-546

 

Ventura S, Luna JM, Cano A. 2016. Big Data on Real-World Applications, InTech, ISBN 978-953-51-2490-0 http://www.intechopen.com/books/big-data-on-real-world-applications

Arodz T, Gao X. 2016. Network Analysis of Inflammation. In: RF Diegelmann, CE Chalfant (Eds.) Frontiers in Inflammation, Vol. 1: Basic Biology and Clinical Aspects of Inflammation, pp. 451-473, Bentham Science, ISBN: 978-1-68108-228-8

Peng Z, Wang C, Uversky VN, Kurgan L. 2016. Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind, In: Zhou Y, Kloczkowski A, Faraggi E, Yang Y, (Eds.), Methods in Molecular Biology, vol. 1484, pp. 187-203, Humana Press, ISBN 978-1-4939-6404-8 http://link.springer.com/protocol/10.1007%2F978-1-4939-6406-2_14

Meng F, Kurgan L. 2016. Computational Prediction of Protein Secondary Structure from Sequence, In: Dunn BM, (Ed.), Current Protocols in Protein Science, unit 86:2.3.1-2.3.10, Wiley, ISBN 978-0-4711-4086-3 http://onlinelibrary.wiley.com/doi/10.1002/cpps.19/full

Arodz T., and Bonchev D. 2015. Identifying influential nodes in a wound healing-related network of biological processes using mean first-passage time. New Journal of Physics 17:025002, IF: 3.558

Cano A., Luna J.M., Gibaja E.L., and Ventura S. 2015. LAIM discretization for multi-label data. Information Sciences, pp 1-15, IF: 4.03.

Luna J.M., Cano A., Pecheniskiy M., and Ventura S. 2015. Speeding-up Association Rule Mining with Inverted Index Compression. IEEE Transactions on Cybernetics, pp 1-15, http://dx.doi.org/10.1109/TCYB.2015.2496175IF: 3.46

Cano A., Luna J.M., Zafra A., and Ventura S. 2015. A Classification Module for Genetic Programming Algorithms in JCLEC. Journal of Machine Learning Research, vol. 16, pp 491-494, http://jmlr.org/papers/volume16/cano15a/cano15a.pdfIF: 2.47

Cano A., Yeguas E., Munoz R., Medina R., and Ventura S. 2015. Parallelization Strategies for Markerless Human Motion Capture. Journal of Real-Time Image Processing, pp 1-15, http://dx.doi.org/10.1007/s11554-014-0467-1IF: 2.02.

Cano A., Zafra A., and Ventura S. 2015. Speeding up multiple instance learning classification rules on GPUs. Knowledge and Information Systems, 44(1), pp 127-145, http://dx.doi.org/10.1007/s10115-014-0752-0IF: 1.78

Cano A., Ventura S. and Cios KJ. 2015. Multi-Objective Genetic Programming for Feature Extraction and Data Visualization. Soft Computing, October 26, pp1-21, http://link.springer.com/article/10.1007/s00500-015-1907-y, IF 1.3

Marquez-Vera C., Cano A., Romero C., Yousef A., Mousa H., and Ventura S. 2015. Early Dropout Prediction using Data Mining: A Case Study with High School Students. Expert Systems, pp 1-20, IF: 0.76

Tao Jing, Xing Wei, Wei Cheng, Mingyang Guan, Yan Huo, Xiuzhen Cheng, “An Efficient Scheme for Tag Information Update in RFID Systems on Roads” in press IEEE Transactions on Vehicular Technology. IF: 1.978

Wei Zhou, Tao Jing, Wei Cheng, Tao Chen, Yan Huo, “Combinatorial auction based spectrum allocation under heterogeneous supply and demand”, in Elsevier Computer Communications, vol. 60, pp. 109-118, April 2015. IF: 1.69

Tao Jing, Xuewei Cui, Wei Cheng, Shixiang Zhu, Yan Huo, Xiuzhen Cheng, “Enabling Smartphone Based HD Video Chats by Cooperative Transmissions in CRNs”, in EURASIP Journal on Wireless Communications and Networking, vol.2015, no.1, March 2015. IF: 0.72

Tao Jing, Fan Zhang, Wei Cheng, Yan Huo, Xiuzhen Cheng, “Online Auction Based Relay Selection for Cooperative Communication in CR Networks”, in EURASIP Journal on Wireless Communications and Networking, vol.2015, no.1, February 2015. IF: 0.72

Yuan Le, Liran Ma, Wei Cheng, Xiuzhen Cheng, Biao Chen, “A Time Fairness Based MAC Algorithm for Throughput Maximization in 802.11 Networks”, in IEEE Transactions on Computers, vol.64, no.1, pp.19-31, January 2015. IF: 1.659

David S Jackson, Wanyu Zang, Qijun Gu, Wei Cheng, Meng Yu, “Exploiting and Defending Trust Models in Cooperative Spectrum Sensing”, in EURASIP Journal on Wireless Communications and Networking,vol.2015, no.1, January 2015. IF: 0.72

Nguyen DT and Cios KJ. 2015. OneClass-DS Algorithm. Applied Soft Computing, October 2015, (35) 267-279, IF 2.8

Higuera C, Gardiner KJ and Cios KJ. 2015. Self-organizing Feature Maps Identify Proteins Critical to Learning in a mouse model of Down Syndrome. PloS One, published June 25, 2015, DOI: 10.1371/journal.pone.0129126. IF 3.2

Damevski K, Shepherd D, Pollock L. “A Field Study of How Developers Locate Features in Source Code”, Journal of Empirical Software Engineering, pp: 1-24, 2015. http://dx.doi.org/10.1007/s10664-015-9373-9. IF 2.2

Wang J, Damevski K, Chen H. “Sensor Data Modeling and Validating for Wireless Soil Sensor Networks”, Journal of Computers and Electronics in Agriculture, vol.112, pp.75-82, 2015. IF 1.8

Mishra, T. N. Dinh, M. T. Thai, J. Seo, I. Shin, Optimal Packet Scan Against Malicious Attacks in Smart Grids, Theoretical Computer Science (TCS), 2015, IF: 0.66

N. Dinh and M. T. Thai, Towards Optimal Community Detection: From Trees to General Weighted Networks, Internet Mathematics, 2015, DOI:10.1080/15427951.2014.950875 

Bahman Rashidi, and Carol Fung, "A Survey of Android Security Threats and Defenses". In Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA), Vol. 6, No. 3, September 2015.

Bahman Rashidi, and Carol Fung, "Disincentivizing Malicious Users in RecDroid Using Bayesian Game Model". In Journal of Internet Services and Information Security (JISIS), Vol. 5, No. 2, May 2015.

Gharibian, Y. Huang, Z. Landau, S. W. Shin. Quantum Hamiltonian Complexity. Foundations and Trends in Theoretical Computer Science, 10 (3):159-282, 2015. http://dx.doi.org/10.1561/0400000066

Gharibian, Z. Landau, S. W. Shin, and G. Wang. Tensor network non-zero testing. Quantum Information & Computation 15 (9 & 10):885-899, 2015. IF 1.393.

Abdelzaher, A, Al-Musawi, A, Mayo, M, Perkins, E and Ghosh, P. Transcriptional Network growing Models using motif based preferential attachment, Frontiers in Bioengineering & Biotechnology, 2015, Oct 12;3:157. http://dx.doi.org/10.3389/fbioe.2015.00157. eCollection 2015. IF: not yet published.

Diego CB Mariano, Felipe L Pereira, Debmalya Barh, Preetam Ghosh, Rommel TJ Ramos, Vasco AC Azevedo. MapRepeat: an approach for effective assembly of repetitive regions in prokaryotic genomes, Bioinformation, 2015, 11(6): 276–279. doi:  10.6026/97320630011276 , IF: 0.5.

Folador, E.L., de Oliveira Junior, A.F., Tiwari, S, Jamal, S.B., Ferreira, R.S., Barh, Ghosh, P, D, Silva, A, Azevedo, V. In silico Prediction of Protein-Protein Interactions: avoiding data and method biases over sensitivity and specificity. Current Protein and Peptide Science, 2015, 16(8):689-700. DOI: 10.2174/1389203716666150505235437 IF: 3.154.

Mayo, M, Abdelzaher, A, Ghosh, P. Long range degree correlations in complex networks, Computational Social Networks, 2015, 2:4, 1-13. http://dx.doi.org/10.1186/s40649-015-0011-x IF: not yet published.

Abdelzaher, M. Mayo, E. Perkins and P. Ghosh. Contribution of Canonical Feed-forward Loop Motifs on the Fault-tolerance and Information Transport Efficiency of Transcriptional Regulatory Networks, Elsevier Nano Communication Networks 2015, 6:3, pp. 133-144. doi:10.1016/j.nancom.2015.04.002 IF: 0.678

Nalluri, J, Kamapantula, B, Barh, D, Azevedo, V, Almeida, S, Silva, A, Ramos, T, Jain, N, Bhattacharya, A, Ghosh, P. DISMIRA: Prioritization of disease candidates in miRNA-disease associations based on maximum weighted matching inference model and motif-based analysis. BMC Genomics, 2015, 16(Suppl 5):S12  doi:10.1186/1471-2164-16-S5-S12. IF: 3.99

Barh, D, Kamapantula, B, Jain, N, Nalluri, J, Juneja, L, Barve, N, Bhattacharya, A, Kumar, A, Miyoshi, A, Azevedo, V, Blum, K, Silva, A, Ghosh, P. miRegulome: a knowledge-base of miRNA regulomics and analysis. Nature Scientific Reports, 2015, 5: 12832. doi:  10.1038/srep12832 IF: 5.578

Wang C, Hu G, Wang K, Brylinski M, Xie L, Kurgan L. “PDID: Database of Molecular-level Putative Protein–drug Interactions in the Structural Human Proteome”, Bioinformatics, published October 26, 2015, DOI:10.1093/bioinformatics/btv597 IF 4.98

Hu G, Wu Z, Wang K, Uversky VN, Kurgan L. “Untapped Potential of Disordered Proteins in Current Druggable Human Proteome”. Current Drug Targets, published July 22, 2015 PMID:26201486 IF 3.02

Yan Y, Friedrich S, Kurgan L. “A Comprehensive Comparative Review of Sequence Based Predictors of DNA and RNA Binding Residues”. Briefings in Bioinformatics, published May 1, 2015, DOI:10.1093/bib/bbv023 IF 9.62

Peng Z, Kurgan L. “High-throughput Prediction of RNA, DNA, AND Protein Binding Regions Mediated by Intrinsic Disorder”. Nucleic Acids Research, 43(18):e121, 2015 IF 9.11

Wu Z, Hu G, Yang J, Peng Z, Uversky VN, Kurgan L. “In Various Protein Complexes, Disordered Protomers Have Large Per-residue Surface Areas and Area of Protein-, DNA- and RNA Binding Interfaces”, FEBS Letters, 589(19):2561-2569, 2015 http://www.sciencedirect.com/science/article/pii/S0014579315007139IF 3.17

Fan X, Kurgan L. “Comprehensive Overview and Assessment of Computational Prediction of MicroRNA Targets in Animals”. Briefings in Bioinformatics, 16(5):780-794, 2015 https://www.ncbi.nlm.nih.gov/pubmed/25471818IF 9.62

Meng F, Badierah R, Almehdar H, Redwan E, Kurgan L, Uversky VN. “Unstructural Biology of the Dengue Virus Proteins”. FEBS Journal, 282(17):3368-3394, 2015 http://onlinelibrary.wiley.com/doi/10.1111/febs.13349/abstractIF 4.00

Ferreira LA, Fan X, Madeira P, Kurgan L, Uversky VN, Zaslavsky B. “Analyzing the effects of protecting osmolytes on solute–water interactions by solvatochromic comparison method: II. Globular proteins”. RSC Advances, 5:59780-59791, 2015 IF 3.84

Chen K, Wang D, Kurgan L. “Systematic Investigation of Sequence and Structural Motifs that Recognize ATP”. Computational Biology and Chemistry, 56:131-141, 2015 http://www.sciencedirect.com/science/article/pii/S1476927115000584IF 1.18

Peng Z, Yan J, Fan, X, Mizianty MJ, Xue B, Wang K, Hu G., Uversky VN, Kurgan L. “Exceptionally Abundant Exceptions: Comprehensive Characterization of Intrinsic Disorder in All Domains of Life”. Cellular and Molecular Life Sciences, 72(1):137-15, 2015 http://link.springer.com/article/10.1007%2Fs00018-014-1661-9IF 5.81

Derr, M. Manic, "Wireless Sensor Networks - Node Localization for Various Industry Problems," in IEEE Transactions on Industrial Informatics, vol. 11, no. 3, pp. 752-762, Jan. 2015, DOI: 10.1109/TII.2015.2396007, IF 8.2

Lewinski, N. and McInnes, B.T. Using natural language processing techniques to inform research on nanotechnology. Beilstein J. Nanotechnol. 2015, 6, 1439-1449. http://www.beilstein-journals.org/bjnano/single/articleFullText.htm?publicId=2190-4286-6-149. IF 2.67

McInnes, B.T. and Pedersen, T. Evaluating Semantic Similarity and Relatedness over the Semantic Grouping of Clinical Term Pairs. Journal of Biomedical Informatics. 2015 Apr; 54:329-336. IF 2.126.

Moon, S., McInnes, B.T. and Melton, G.B. Challenges and Practical Approaches with Word Sense Disambiguation of Acronyms and Abbreviations in the Clinical Domain. Healthcare informatics research, 2015, 21 (1), 35-42. http://synapse.koreamed.org/DOIx.php?id=10.4258/hir.2015.21.1.35.

Cios KJ and Nguyen DT. 2015. Data Mining and Data Visualization (Chapter 20, 294-323). In: Routledge International Handbook of Advanced Quantitative Methods in Nursing Research, Henly SJ (ed.)

Bulut E., and Szymanski B., "Understanding User Behavior via Mobile Data Analysis", in Proc. of IEEE ICC (International Conference on Communications) Workshops, pp. 1548-1553, June 8, London, UK, 2015.Pinheiro D., Cano A., and Ventura S. Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE. EPIA 2015 (Portuguese Conference on Artificial Intelligence), September 8-11, 2015, Coimbra, Portugal.

Bo Mei, Wei Cheng, Xiuzhen Cheng, “Fog Computing Based Ultraviolet Radiation Measurement via Smartphones”, in HotWeb 2015, Nov. 12-13, 2015, Washington DC.

Xiaolu Cheng, Jessica Lu, Wei Cheng, “A Survey on RFID Applications in Vehicle Networks”, in IIKI 2015, Oct. 22-23, Beijing, China.

Wei Cheng, Xiaolu Cheng, Dechang Chen, “Utilizing RSS-Ratio for Implementing Anonymous Communications in VANETs”, in ICCVE 2015, Oct. 19-23, Shenzhen, China.

Wei Cheng, Feng Chen, Xiuzhen Cheng, “Controlling the Spreads of Infectious Disease and Scare via Utilizing Location and Social Networking Information” in ACM Mobihoc 2015 workshops on Mobile Big Data, pp. 1-5, June 22-25, 2015, Hangzhou, China.

Zubair S. and Cios KJ. 2015. Extracting News Sentiment and Establishing its Relationship with the S&P 500 Index. HICSS’2015 (Hawaii International Conference on System Sciences), January 5-8, 2015, Kauai

Corley C, Damevski K, Kraft N. “Exploring the Use of Deep Learning for Feature Location”. ICSME 2015 (International Conference on Software Maintenance and Evolution), Sept. 29 – Oct. 1, 2015, Bremen, Germany.

Shepherd D, Damevski K, Pollock L. “How and When to Transfer Software Engineering Research via Extensions”. ICSE 2015 (International Conference on Software Engineering), May 18 – 22, 2015. Florence, Italy.

Damevski K, Shepherd D, Pollock L. “Scaling up Evaluation of Code Search Tools through Developer Usage Metrics”. SANER 2015 (IEEE International Conference on Software Analysis, Evolution, and Reengineering), March 2-6, 2015, Montreal, Canada.

Damevski K, Shepherd D, Kraft N, Pollock L. “Supporting Developers in Porting Software via Combined Textual and Structural Analysis of Software Artifacts”. CSESSP 2015 (NITRD Workshop on Computational Science & Engineering Software Sustainability and Productivity Challenges). October 14-16, 2015.

N. Dinh, X. Li, and M. T. Thai, Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits, The IEEE International Conference on Data Mining (ICDM), 2015. Regular paper, Acceptance rate: 8.4%)

Nguyen, T. N. Dinh, and T. Vu, Community Detection in Multiplex Social Networks, IEEE Workshop on Inter-Dependent Networks, INFOCOM (WIDN), 2015.

N. Dinhand M. T. Thai, Assessing Attack Vulnerability in Networks with Uncertainty, in Proceedings of the IEEE Int Conference on Computer Communications (INFOCOM), 2015 (acceptance rate: 19%).

T. Nguyen and T. N. Dinh, Unveiling the Structure of Multi-attributed Networks via Joint Non-negative Matrix Factorization, in Proceedings of the IEEE Military Communications Conference (MILCOM), 2015.

N. Dinh and R. Tiwari, Breaking Bad: Finding Triangle-Breaking Points in Large Networks, International Conference on Computational Social Networks (CSoNet), 2015. DOI:10.1007/978-3-319-21786-4_25

Dinh, T, Nguyen, H, Ghosh, P, Mayo, M. Social Influence Spectrum with Guarantees: Computing More in Less Time, Lecture Notes in Computer Science, LNCS 9197, Proceedings of the 4th International Conference on Computational Social Networks (CSoNet 2015), 84-103. http://dx.doi.org/10.1007/978-3-319-21786-4_8 (Best paper award)

Huanhuan Zhang, Jie Zhang, Carol Fungand Chang Xu. "Improving Sybil Detection via Graph Pruning and Regularization Techniques". In 7th Asian Conference on Machine Learning (ACML). November, 2015, Hong Kong.

Carol Fung and Bill McCormick. "VGuard: A Distributed Denial of Service Attack Mitigation Method using Network Function Virtualization". In 11th International Conference on Networks and Sevice Management (CNSM'15). Mini Conference Track. Barcelona, Spain.

Shaohan Huang, Carol Fung, Kui Wang, Yaqi Yang, Zhongzhi Luan, and Depei Qian. "Revisit Network Anomaly Ranking in Datacenter Network Using Re-ranking". In 4th IEEE International Conference on Cloud Computing (CloudNet'15). Niagara Falls, Canada.

Andrzej Kamisiński, and Carol Fung. "FlowMon: Detecting Malicious Switches in Software-Defined Networks". In ACM CCS workshop on Automated Decision Making for Active Cyber Defense 2015 (Safeconfig 2015). Denver, Colorado.

Bahman Rashidi, Carol Fung, Gerrit Bond, Steven Jackson, Marcus Pare, and Tam Vu. "RecDroid: An Android Resource Access Permission Recommendation System." ACM MobiHoc 2015. Demo paper. Hangzhou, China.

Chao Ding, Carol Fung, Kui Wang, Polo Peiz, You Meng, Zhongzhi Luan, Depei Qian. "A Methodology for Root-cause Analysis in Component Based Systems." IEEE/ACM International Symposium on Quality of Service (IWQoS) 2015. Short paper. Portland, Oregon.

Bahman Rashidi and Carol Fung. "A Game-Theoretic Model for Defending Against Malicious Users in RecDroid." Proceedings of the IEEE/IFIP IM2015 Workshop on Security for Emerging Distributed Network Technologies (DISSECT'15).

Lei Wei and Carol Fung. FlowRanger: "A Request Prioritizing Algorithm for Controller DoS Attacks in Software Defined Networks." IEEE International Conference on Communications (ICC 2015). London, UK.

Ioana Bara, Carol Fung, and T. N. Dinh. "Enhancing Twitter Spam Accounts Discovery Using Cross-Account Pattern Mining." IFIP/IEEE International Symposium on Integrated Network Management (IM 2015). Mini Conference. Ottawa, Canada.

Bahman Rashidi, Carol Fung, and Tam Vu. "Dude, Ask The Experts!: Resource Access Permission Recommendation with RecDroid." IFIP/IEEE International Symposium on Integrated Network Management (IM 2015). Main Track. Ottawa, Canada.

Gharibian, J. Sikora. Ground state connectivity of local Hamiltonians. Proceedings of the 42^nd International Colloquium on Automata, Languages and Programming (ICALP), volume 9134 of Lecture Notes in Computer Science, pages 617 – 628, 2015, Kyoto, Japan.

Abdelzaher, T. Dinh, M. Mayo, P. Ghosh. Optimal topology of gene-regulatory networks: role of the average shortest path, Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015, pp. 1-4.

Pidaparti, S. Das and P. Ghosh. An Algorithm for Curvature Conformation in Microtubule Self-Assembly, Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015, pp. 1-4.

Nalluri, P. Rana, V. Azevedo, D. Barh and P. Ghosh. Determining influential miRNA targets in diseases using influence diffusion model,BCB '15, Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics, 519-20. doi>10.1145/2808719.2811440

Rana, P. Ghosh, K.R. Pilkiewicz, E.J. Perkins, C. Warner, M.L. Mayo. Capacity estimates of additive inverse Gaussian molecular channels with relay characteristics. Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015, pp. 1-4.

Khajamoinuddin S, B. K. Kamapantula, M. Mayo, E. Perkins, P. Ghosh. Abundance of connected motifs in transcriptional networks, a case study using random forests regression. Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2015, pp. 1-8.

Nazi, A, Raj, M, Francesco, M.D, Ghosh, P, Das, S.K. Exploiting Gene Regulatory Networks for Robust Wireless Sensor Networking, Proceedings of the 2015 IEEE Global Communications Conference (GLOBECOM), pp. 1-6. http://globecom2015.ieee-globecom.org/content/technical-symposium-program-all-papers

Ghosh P., Kumar, A., Rangachari V. and Vaidya, A. Determination of Nucleation Mass for Amyloid-β Aggregation. Biophysical Journal 2015, 108(2), 525a.

Kecman V., Iterative k Data Algorithm for Solving Both The Least Squares SVM and The System of Linear Equations, Proceedings of the IEEE South-East Conf., Fort Lauderdale, FL, March, 2015

Amarasinghe, D. Wijayasekara, H. Carey, M. Manic, D. He, W. Chen, "Artificial Neural Networks based Thermal Energy Storage Control for Buildings," in Proc. 41st Annual Conference of the IEEE Industrial Electronics Society, IEEE IECON 2015, Yokohama, Japan, Nov. 09-12, 2015.

Wijayasekara, M. Manic, "Data-Fusion for Increasing Temporal Resolution of Building Energy Management System Data," in Proc. 41st Annual Conference of the IEEE Industrial Electronics Society, IEEE IECON 2015, Yokohama, Japan, Nov. 09-12, 2015. (Best student paper award)

Amarasinghe, M. Manic, R. Hruska, "Optimal Stop Word Selection for Text Mining in Critical Infrastructure Domain," in Proc. IEEE Symposium on Resilience Control Systems, ISRCS 2015, Philadelphia, PA, Aug. 18-20, 2015.  DOI: 10.1109/RWEEK.2015.7287440

Wijayasekara, M. Manic, D. Gertman, "Data Driven Fuel Efficient Driving Behavior Feedback for Fleet Vehicles," in Proc. of IEEE 8th International Conference on Human System Interaction, IEEE HSI 2015, Warsaw, Poland, June 25-27, 2015.  DOI: 10.1109/HSI.2015.7170646(Best paper award)

Joël Alwen, Rafail Ostrovsky, Hong-Sheng Zhou, Vassilis Zikas: Incoercible Multi-party Computation and Universally Composable Receipt-Free Voting. CRYPTO (2) 2015: 763-780

Dana Dachman-Soled, Feng-Hao Liu, Hong-Sheng Zhou: Leakage-Resilient Circuits Revisited - Optimal Number of Computing Components Without Leak-Free Hardware. EUROCRYPT (2) 2015: 131-158

Dov Gordon, Jonathan Katz, Feng-Hao Liu, Elaine Shi, Hong-Sheng Zhou: Multi-Client Verifiable Computation with Stronger Security Guarantees. TCC (2) 2015: 144-168

Dana Dachman-Soled, Feng-Hao Liu, Elaine Shi, Hong-Sheng Zhou: Locally Decodable and Updatable Non-malleable Codes and Their Applications. TCC (1) 2015: 427-450

Luna J.M., Cano A., and Ventura S. 2015. Genetic Programming for Mining Association Rules in Relational Database Environments. In Handbook of Genetic Programming Applications, Springer, ISBN 978-3-319-20882-4

Luna J.M., Cano A., and Ventura S. 2015. An Evolutionary Self-Adaptive Algorithm for Mining Association Rules. In Data Mining: Principles, Applications and Emerging Challenges, Nova Publishers, ISBN 978-1-63463-770-1

Snipes W, Murphy-Hill E, Fritz T, Vakilian M, Damevski K, Nair A, Shepherd D. 2015. A Practical Guide to Analyzing IDE Usage Data (Chapter 5, 85-136). In: The Art and Science of Analyzing Software Data, Bird C, Menzies T, Zimmerman T (ed.)

Xinlei Wang, Wei Cheng, Prasant Mohapatra, Abdelzaher, T. “Enabling Reputation and Trust in Privacy-Preserving Mobile Sensing” in IEEE Transactions on Mobile Computing, vol. 13, no. 12, pp. 2777-2790, December 2014. IF: 2.912 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6671556

Yanfei Lu, Xin Li, Xing Wei, Tao Jing, Wei Cheng, Yan Huo, “Secured access control for vehicles in RFID systems on roads” in Personal and Ubiquitous Computing, vol. 18, no. 8, pp. 1893-1900, September 2014. IF: 1.616 http://link.springer.com/article/10.1007%2Fs00779-014-0794-z

Wei Cheng, Shengling Wang, Xiuzhen Cheng, “Virtual Track: Applications and Challenges of the RFID System on Roads”, in IEEE Network, vol. 28, no. 1, pp 42-47, January 2014. IF: 3.72 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6724105

Strack B, Jacobs K and Cios KJ. 2014. Simulating vertical and horizontal inhibition with short term dynamics in a multi-column multi-layer model of Neocortex. International Journal of Neural Systems, 24(5): 1440002 (2014) [19 pages] DOI: 10.1142/S0129065714400024. IF: 6.056 http://www.worldscientific.com/worldscinet/ijns

Strack B, Olmo J, DeShazo, Jennings C, Cios KJ and Clore JN. 2014. Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records. Hindawi Publishing Corp.: BioMed Research International, Volume 2014 (2014), Article ID 781670, 11 pages, http://dx.doi.org/10.1155/2014/781670, IF: 2.706 http://www.hindawi.com/journals/bmri/

Cano A, Nguyen DT, Ventura S and Cios KJ. 2014. ur-CAIM: An Improved CAIM Discretization Algorithm for Unbalanced and Balanced Data Sets. Soft Computing, October, DOI: 10.1007/s00500-014-1488-1, IF: 1.304 http://www.springer.com/engineering/computational+intelligence+and+complexity/journal/500

Cano A, Ventura S and Cios KJ. 2014. Scalable CAIM Discretization on Multiple GPUs Using Concurrent Kernels. The Journal of Supercomputing, July 2014, 69(1), pp 273-292, DOI: 10.1007/s11227-014-1151-8, IF: 0.841 http://www.springer.com/computer/swe/journal/11227

N. P. Nguyen, T. N. Dinh, Y. Shen, and My T. Thai, Dynamic social community detection and its applications, PLoS ONE, 2014. IF: 3.534 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0091431

T. N. Dinh and M. T. Thai, Network under Joint Node and Link Attacks: Vulnerability Assessment Methods and Analysis, IEEE/ ACM Transactions on Networking (ToN), 2014. IF:1.986, http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6805229

T. N. Dinh, H. Zhang, Y. Shen, D. T. Nguyen, and M. T. Thai, Cost-effective Viral Marketing for Time-critical Campaigns in Large-scale Social Networks, IEEE/ ACM Transactions on Networking (ToN), 2014. IF: 1.986 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6678627

N. P. Nguyen, M. A. Alim, T. N. Dinh, M. T. Thai, A method to detect communities with stability in social networks, Social Network Analysis and Mining, 2014 http://link.springer.com/article/10.1007%2Fs13278-014-0224-2

Y Shen, T. N Dinh, M. T. Thai, HT Nguyen, Staying safe and visible via message sharing in online social networks, Journal of Combinatorial Optimization 28 (1), 186-217, 2014. IF: 1.043 http://link.springer.com/article/10.1007%2Fs10878-013-9667-z

T. N. Dinh and M. T. Thai, Bound and Exact Methods for Assessing Link Vulnerability in Complex Networks, Journal of Combinatorial Optimization (JOCO), 2014, IF: 1.043 http://link.springer.com/article/10.1007%2Fs10878-014-9742-0

S. Gharibian, J. Kempe. Hardness of approximation for quantum problems, Quantum Information & Computation 14 (5 & 6): 517-540, 2014. IF: 1.625

D. Berry, R. Cleve, S. Gharibian. Gate-efficient discrete simulations of continuous-time quantum query algorithms. Quantum Information & Computation 14 (1 & 2): 0001-0030, 2014. IF: 1.625

Mayo, M, Abdelzaher, A, Perkins, EJ, Ghosh, P. Top-level dynamics and the regulated gene response of feed-forward loop transcriptional motifs. Physical Review E, 90:3, pp. 032706-1 – 032706-12, 2014, IF: 2.326

Nazi, A, Raj, M, Francesco, M, Ghosh, P, Das, S.K. Deployment of Robust Wireless Sensor Networks using Gene Regulatory Networks: an Isomorphism-based Approach, Pervasive and Mobile Computing, 13, pp. 246-257, 2014, IF: 1.667.

Pokrajac D., Lazarevic A., Kecman V., Marcano A., Markushin Y., Vance T., Reljin N., McDaniel S., Melikechi N., Automatic Classification of Laser-Induced Breakdown Spectroscopy (LIBS) Data of Protein Biomarker Solutions, Applied Spectroscopy, Vol. 68, Iss. 9, pp. 1067-1075, 2014 IF: 2.014

D. Wijayasekara, O. Linda, M. Manic, C. Rieger, "Mining Building Energy Management System Data Using Fuzzy Anomaly Detection and Linguistic Descriptions," in IEEE Transactions on Industrial Informatics, vol. 10, no. 3, pp. 1829-1840, 03 June 2014. DOI: 10.1109/TII.2014.2328291. IF: 8.785

D. Wijayasekara, O. Linda, M. Manic, C. Rieger, "FN-DFE: Fuzzy-Neural Data Fusion Engine for Enhanced Resilient State-Awareness of Hybrid Energy Systems," Accepted for publication in IEEE Transactions on Cybernetics, May 2014.  DOI: 10.1109/TCYB.2014.23238913. IF: 3.236

T. Vollmer, M. Manic, O. Linda, "Autonomic Intelligent Cyber Sensor to Support Industrial Control Network Awareness," in IEEE Transactions on Industrial Informatics, vol. 10, no. 2, pp. 1647-1658, May 2014.  DOI: 10.1109/TII.2013.2270373. IF: 8.785

T. Vollmer, M. Manic, "Cyber-Physical System Security with Deceptive Virtual Hosts for Industrial Control Networks," in IEEE Transactions on Industrial Informatics, vol. 10, no. 2, pp. 1337-1347, May 2014.  DOI: 10.1109/TII.2014.2304633. IF: 8.785

B.T. McInnes and M. Stevenson. Determining the difficulty of word sense disambiguation. Journal of Biomedical Informatics. 2014 Feb; 47:83-90, doi: 10.1016/j.jbi.2013.09.009, IF: 2.482

Xiangyu Liu, Bin Wang, Xiaochun Yang, Meng Yu, Wanyu Zang, Obtaining K-obfuscation for profile privacy in social networks. Security and Communication Networks 7(9): 1384-1398 (2014) http://onlinelibrary.wiley.com/doi/10.1002/sec.871/abstract;jsessionid=8FEB08F7D571853240A8042AD67BDF02.f04t04, IF 0.433

Yan Huo, Yumeng Lu, Wei Cheng, Tao Jing, “Vehicle Road Distance Measurement and Maintenance in RFID Systems on Roads”, in IEEE ICCVE 2014, Nov. 3-7, Austria. http://www.iccve.orgTao Jing, Fan Zhang, Wei Cheng, Yan Huo, Xiuzhen Cheng, “Online Auction Based Relay Selection for Cooperative Communications in CR Networks”, in WASA 2014, June 2014, China.

David Jackson, Wanyu Zang, Qijun Gu, Wei Cheng “Exploiting and Defending Trust Models in Cooperative Spectrum Sensing”, in WASA 2014, June 2014, China.

Tao Jing, Xuewei Cui, Wei Cheng, Shixiang Zhu, Yan Huo, “Enabling Smartphone Based HD Video Chats by Cooperative Transmissions in CRNs”, in WASA 2014, June 2014, China.

Wei Cheng, Jindan Zhu, Prasant Mohapatra, Jie Wang, “Time and Energy Efficient Localization”, in IEEE SECON 2014, June 2014, Singapore. http://secon2014.ieee-secon.org

Y. Song and T. N. Dinh, Optimal Containment of Misinformation in Social Media: A Scenario-based Approach, International Workshop on Computational Networks (CSoNet), Hawaii, Lecture Note in Computer Science, 2014 http://link.springer.com/chapter/10.1007%2F978-3-319-12691-3_40

Md. A. Alim, N. P. Nguyen, T. N. Dinh, and M. T. Thai, Vulnerability Analysis of Overlapping Communities in Complex Networks, in Proceedings of the 2014 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2014 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6927519

S. Mishra, T. N. Dinh, and M. T. Thai, Optimal Inspection Points for Malicious Attack Detection in Smart Grids, The 20th International Computing and Combinatorics Conference (COCOON), 2014, http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6927519

Bahman Rashidi, Carol Fung, and Tam Vu, “RecDroid: A Resource Access Permission Control Portal and Recommendation Service for Smartphone Users”. Workshop on Security and Privacy Aspects of Mobile Environment. 2014 (SPME14), http://dl.acm.org/citation.cfm?id=2646586

Carol Fung, M. Gharbaoui, F. Paolucci, A. Giorgetti, P. Castoldi, and B. Martini, “Quality of Interaction among Path Computation Elements for Trust-aware Inter-Provider Cooperation”. IEEE International Conference on Communications (ICC14), Sydney, Australia, 2014 http://icc2014.ieee-icc.org/

Carol Fung, Disney Lam, and Raouf Boutaba, “RevMatch: An Efficient and Robust Decision Model for Collaborative Malware Detection”. IEEE/IFIP Network Operation and Management Symposium (NOMS14). Krakow, Poland, 2014 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6838251

S. Gharibian, Z. Landau, S. W. Shin, G. Wang. Tensor network non-zero testing, 14th Asian Quantum Information Science Conference (AQIS), August 20-24, 2014, in Kyoto, Japan. Presented by S. W. Shin.

S. Gharibian, J. Kempe. Hardness of approximation for quantum problems, ELC Workshop on Inapproximability, January 25-26, 2014, at University of Electro-Communications, Chofu, Japan. Invited talk.

M. Mayo, A. Abdelzaher, B. Kamapantula, E. Perkins, and P. Ghosh, Networks of interactions between feed-forward loop transcriptional motifs in gene-regulatory networks, BICT 2014, pp.1-4.

B. Kamapantula, M. Mayo, E. Perkins, A. Abdelzaher and P. Ghosh, Feature ranking in transcriptional networks: Packet receipt as a dynamical metric, BICT 2014, pp. 1-8, Best student paper award.

A. Abdelzaher, M. Mayo, E. Perkins and P. Ghosh. Correlating In silico Feed-forward Loop Knockout Experiments with the Topological Features of Transcriptional Regulatory Networks, BICT 2014, pp. 1-8.

B. K. Kamapantula, M. Mayo, E. Perkins and P. Ghosh. Dynamical impacts from structural redundancy of transcriptional motifs in gene-regulatory networks, BICT 2014, pp. 1-8.

S. Das, R. Pidaparti and P. Ghosh. Modeling Self-organization of Microtubules from Tubulins, BICT 2014, pp.1-4.

Mayo, M, Abdelzaher, A, Ghosh, P. Mixed Degree-Degree Correlations in Directed Social Networks, LNCS CSoNet, 2014, pp. 571-580, http://link.springer.com/chapter/10.1007%2F978-3-319-12691-3_42.

Ahmed F. Abdelzaher, Ahmad F. Al-Musawi, Preetam Ghosh, David S. Jackson, John A. Palesis and Jonathan P. Deshazo, Variations of Care Coordination Metrics for Sharing Patients among Physicians: A Social Network Analytic Approach, ACM BCB 2014, pp. 635-636.

Winfrey, C.M., Baldwin, B.J., Cummings, M.A., Ghosh, P. OSM: An Evolutionary System of Systems Framework for Modeling and Simulation, ACM SpringSim 2014, pp. 1-8.

Kecman V., Zigic Lj., Algorithms for Direct L2 Support Vector Machines, The IEEE International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2014, 978-1-4799-3020-3/14 ©2014 IEEE, Alberobello, Italy, June 2014 http://www.inista.org/

Zigic Lj., Kecman V., Variants and Performances of Novel Direct Learning Algorithms for L2 Support Vector Machines, in L. Rutkowski et al. (Eds.): ICAISC 2014, Part II, LNAI 8468, pp. 82–91, 2014 http://www.icaisc.eu/

Zigic Lj., Kecman V., Direct L2 Support Vector Machine Classifier and Performances of Its Two Implementations, Proceedings of the IEEE South-East Conf., Lexington, KY, March, 2014 https://ieeexplore.ieee.org/document/6950701

V. Molano, C. Cobos, M. Mendoza, E. Herrera-Viedma, M. Manic, "Feature Selection based on Sampling and C4.5 Algorithm to Improve the Quality of Text Classification using Naive Bayes," Accepted for publication at the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, Tuxtla Gutierrez, Chiapas, Mexico, Nov. 16-24, 2014. http://ieeexplore.ieee.org/abstract/document/1579062/

D. Wijayasekara, M. Manic, "Dynamic Fuzzy Force Field Based Force-Feedback for Collision Avoidance in Robot Manipulators," in Proc. 40th Annual Conference of the IEEE Industrial Electronics Society, IEEE IECON 2014, Dallas, TX- USA, Oct. 29 - Nov. 1, 2014. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7049100

D. Wijayasekara, M. Manic, M. McQueen, "Vulnerability Identification and Classification Via Text Mining Bug Databases," in Proc. 40th Annual Conference of the IEEE Industrial Electronics Society, IEEE IECON 2014, Dallas, TX- USA, Oct. 29 - Nov. 1, 2014.

D. Wijayasekara, M. Manic, "Data Driven Fuzzy Membership Function Generation for Increased Understandability," in Proc. of FUZZ-IEEE, 2014, within, IEEE World Congress On Computational Intelligence, WCCI 2014, Beijing, China, July 6-11, 2014. http://www.ieee-wcci2014.org/

K. McCarty, M. Manic, "Fuzzy Contexts (Type C) and Fuzzymorphism to Solve Situational Discontinuity Problems," in Proc. of FUZZ-IEEE, 2014, within, IEEE World Congress On Computational Intelligence, WCCI 2014, Beijing, China, July 6-11, 2014. http://www.ieee-wcci2014.org/

D. Wijayasekara, M. Manic, "Fuzzy Logic Based Force-Feedback for Obstacle Collision Avoidance of Robot Manipulators," in Proc. of IEEE 7th International Conference on Human System Interaction, IEEE HSI 2014, Lisbon, Portugal, June 16-18, 2014.

D. Wijayasekara, M. Manic, D. Gertman, "Driving Behavior Prompting Framework for Improving Fuel Efficiency," in Proc. of IEEE 7th International Conference on Human System Interaction, IEEE HSI 2014, Lisbon, Portugal, June 16-18, 2014.

K. Amarasinghe, D. Wijayasekara, M. Manic, "EEG based brain activity monitoring using Artificial Neural Networks," in Proc. of IEEE 7th International Conference on Human System Interaction, IEEE HSI 2014, Lisbon, Portugal, June 16-18, 2014.

K. McCarty, M. Manic, "A Database Driven Memetic Algorithm for Fuzzy Set Optimization," in Proc. of IEEE 7th International Conference on Human System Interaction, IEEE HSI 2014, Lisbon, Portugal, June 16-18, 2014.

K. Amarasinghe, D. Wijayasekara, M. Manic, "Neural Network Based Downscaling of Building Energy Management System Data," in Proc. IEEE International Symposium on Industrial Electronics, ISIE 2014, Istanbul, Turkey, June 1-4, 2014. http://www.isie.boun.edu.tr/

O. Linda, D. Wijayasekara, M. Manic, M. McQueen, "Optimal Placement of Phasor Measurement Units in Power Grids Using Memetic Algorithms," in Proc. IEEE International Symposium on Industrial Electronics, ISIE 2014, Istanbul, Turkey, June 1-4, 2014.  http://www.isie.boun.edu.tr/

H. Hess, V. Gupta, D. Wijayasekara, E. William, M. Huff, O. Linda, M. Krei, M. Manic, A. Thakker, F. Rufus, J. Govar, "State of Charge Indicator (SOCI) Design for Li/CFx Battery", in Proc. 2014 Army Power Sources Conference, pp. 1-6, Jun. 9-12, 2014.  http://www.powersourcesconference.com

M. Manic, D. Wijayasekara, K. Amarasinghe, J. Hewlett, K. Handy, C. Becker, B. Patterson, R. Peterson, "Next Generation Emergency Communication Systems via Software Defined Networks," in Proc. GENI Research and Educational Experiment Workshop (GREE 2014) - Jointly with the 19th GENI Engineering Conference (GEC 19), Atlanta Georgia, Mar. 19-20 2014, http://groups.geni.net/geni/wiki/APRAGENI/GREE2014

B.T. McInnes, T. Pedersen, Y. Liu, S. Pakhomov, and G.B. Melton. U-path: An undirected path-based measure of semantic similarity. Appears in the Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), November 2014

Jonathan Katz, Aggelos Kiayias, Hong-Sheng Zhou, Vassilis Zikas, “Distributing the Setup in Universally Composable Multi-Party Computation”, PODC 2014 -- ACM Symposium on Principles of Distributed Computing, http://dl.acm.org/citation.cfm?doid=2611462.2611480

Shafi Goldwasser, Dov Gordon, Vipul Goyal, Abhishek Jain, Jonathan Katz, Feng-Hao Liu, Amit Sahai, Elaine Shi, Hong-Sheng Zhou, “Multi-Input Functional Encryption”, EUROCRYPT 2014 -- Advances of Cryptology http://link.springer.com/chapter/10.1007%2F978-3-642-55220-5_32

Seung Geol Choi, Jonathan Katz, Dominique Schröder, Arkady Yerukhimovich, Hong-Sheng Zhou, “(Efficient) Universally Composable Two-Party Computation Using a Minimal Number of Stateless Tokens”, TCC 2014 -- Theory of Cryptography Conference http://link.springer.com/chapter/10.1007%2F978-3-642-54242-8_27

Min Li, Zili Zha, Wanyu Zang, Meng Yu, Peng Liu, Kun Bai. “Detangling Resource Management Functions from the TCB in Privacy-Preserving Virtualization.” In The 19th European Symposium on Research in Computer Security (ESORICS 2014). September 7-11, 2014, Wroclaw, Poland

Bin Wang, Xiaochun Yang, Wanyu Zang and Meng Yu. “Approximate Self-Adaptive Data Collection in Wireless Sensor Networks.” In The 9th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2014). June 23-25, 2014, Harbin, China https://link.springer.com/chapter/10.1007/978-3-319-07782-6_51

 

Slawek J, Arodz T. ENNET: Inferring Large Gene Regulatory Networks from Expression Data using Gradient Boosting. BMC Systems Biology 7:106, 2013. Impact Factor: 2.98Federici G, Gao X, Slawek J, Arodz T, Shitaye A, Wulfkuhle JD, de Maria R, Liotta LA, Petricoin EF. Systems Level Network Analysis of the NCI-60 Cancer Cell Lines by Alignment of Protein Pathway Activation Modules with Multiple "-omic" Data Fields and Therapeutic Response Signatures. Molecular Cancer Research 11:676-685, 2013. Impact Factor: 4.353

Arodz T, Plonka PM. Sequence and Structure Space Model of Protein Divergence driven by Point Mutations. Journal of Theoretical Biology 330:1-8, 2013. Impact Factor: 2.351

Arodz T, Bonchev D, Diegelmann RF. Network Approach to Wound Healing. Advances in Wound Care 2: 499-509, 2013

Shraboni Jana, Kai Zeng, Wei Cheng, Prasant Mohapatra, “Trusted Collaborative Spectrum Sensing for Mobile Cognitive Radio Networks”, in IEEE Transactions on Information Forensics and Security, vol. 8, no.9, pp. 1497-1507, 2013, Impact Factor 1.895.

Xiaoshuang Xing, Tao Jing, Wei Cheng, Yan Huo, Xiuzhen Cheng, “Spectrum Prediction in Cognitive Radio Networks”, IEEE Wireless Communications, vol. 20, no. 2, pp. 90-96, April 2013, Impact Factor 3.74.

Wei Cheng, Nan Zhang, Min Song, Dechang Chen, Xiuzhen Cheng, “Time-Bounded Essential Localization for Wireless Sensor Networks”, IEEE/ACM Transactions on Networking vol. 21, no.2, pp. 400-412, April 2013, Impact Factor 2.014.

Nguyen DT, Nguyen CD, Hobson R, Kurgan LA and Cios KJ. 2013. mi-DS: Multiple-Instance Learning Algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 43(1)143-154, Impact Factor 3.236

Dinh TNand Thai MT, Community Detection in Scale-free Networks: Approximation Algorithms for Maximizing Modularity, IEEE Journal on Selected Areas in Communications: Special Issue on Network Science (JSAC), Vol. 31, Issue 6, pp. 997-1006, 2013, Impact Factor 3.121

Tiwari R, Dinh TN, and Thai TM, On Centralized and Localized approximation algorithms for Interference-Aware Broadcast Scheduling, IEEE Transaction on Mobile Computing (TMC), Vol. 12, Issue 2, pp. 233-247, 2013, Impact Factor 2.395

Ghag, G, Ghosh P., Mauro, A., Rangachari V. and Vaidya, A. Stability Analysis of 4-species A-beta Aggregation Model: A Novel Approach to Obtaining Physically Meaningful Rate Constants.Applied Mathematics and Computation, 224: 205-215, 2013, Impact factor: 1.349

Santos, AR, Barbosa, E, Fiaux, K, Zurita-Turk, M, Chaitankar, V, Kamapantula, B, Abdelzaher, A, Ghosh, P, Tiwari, S, Barve, N, Jain, N, Barh, D, Silva, A, Miyoshi, A, and Azevedo, V. Pannotator: An automated tool for annotation of pan-genomes. Genet. Mol. Res. 12 (3): 2982 – 2989, 2013, Impact factor: 0.99

Debmalya Barh, Neha Jain, Sandeep Tiwari, John K Field, Elena Padin-Iruegas, Alvaro Ruibal, Rafael López, Michel Herranz, Antaripa Bhattacharya, Lucky Juneja, Cedric Viero, Artur Silva, Anderson Miyoshi, Anil Kumar, Kenneth Blum, Vasco Azevedo, Preetam Ghosh, Triantafillos Liloglou. A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer, BMC Genomics, 14, Suppl 6: S5, 2013, Impact factor: 4.4

Kamapantula, B, Abdelzaher, A, Ghosh, P., Mayo, M., Perkins, E., and Das, S.K. Leveraging the Robustness of Genetic Networks: A Case Study on Bio-inspired Wireless Sensor Topologies. Journal of Ambient Intelligence and Humanized Computing, 2013, DOI : 10.1007/s12652-013-0180-0, Impact factor: 1.77

Barh, D, Gupta, K, Jain, N, Khatri, G, Leon Sicairos, N, Tiwari, S, Rahangdale, S, Verma, A, Hassan, S, Rodrigues dos Santos, A, Ali, A, Thiao Juca Ramos, R, Miyoshi, A, Silva, A, Kumavath, R, Kumar, A, Ghosh, P, Blum, K, Misra, AN and Azevedo, V. Globally conserved inter-species bacterial PPIs based conserved host-pathogen interactome derived novel target in C. pseudotuberculosis, C. diptheriae, M. tuberculosis, C. ulcerans, Y. pestis and E. coli targeted by Piper betel compounds, Journal of Integrative Biology, 2013, Impact factor: 4.321

Strack R., Kecman V., Strack B., Li Q., Sphere Support Vector Machines for Large Classification Tasks, Neurocomputing, Vol. 101, pp. 59–67, 2013, Impact Factor 1.634

Li Q., Salman R., Test E., Strack R., Kecman V., Parallel Multi-task Cross Validation for Support Vector Machine Using GPU, Journal of Parallel and Distributed Computing, Vol. 73, Issue 3, pp. 293-302, 2013, 1.116

Chengpo Mu, Meng Yu, Yingjiu Li, Wanyu Zang. “Risk balance defense approach against intrusions for network server.” International Journal of Information Security. October 2013. http://link.springer.com/article/10.1007%2Fs10207-013-0214-9.

Yan Yang, Yulong Zhang, Alex Hai Wang, Meng Yu, Wanyu Zang, Peng Liu, Sushil Jajodia,“Quantitative survivability evaluation of three virtual machine-based server architectures”. Journal of Network and Computer Applications, Volume 36, Issue 2, March 2013, Pages 781–790.

Gao X, Arodz T. Detecting Differentially Co-expressed Genes for Drug Target Analysis. In: "Proc. International Conference on Computational Science ICCS'2013, Barcelona, Spain, 5-7 June", Procedia Computer Science 18:1392-1401, Elsevier, 2013.Tao Jing, Xing Wei, Wei Cheng, Mingyang Guan, Yan Huo, “Emergent Information Diffusion in RFID Systems on Roads”, in IEEE ICCVE 2013, December 2-6, 2013, Las Vegas, USA.

Tao Jing, Xingni Li, Wei Cheng, Yan Huo, “Speeding Detection in RFID Systems on Roads”, in IEEE ICCVE 2013, December 2-6, 2013, Las Vegas, USA.

Wei Cheng, “Engineering Challenges in RFID Systems on Roads”, in ICAPEM 2013, Nov. 21-22, 2013, Shanghai, China.

Yanfei Lu, Xin Li, Xing Wei, Tao Jing, Wei Cheng, Yan Huo, “Secured Access Control for Vehicles in RFID Systems on Roads” in IIKI 2013, October 18-20, 2013, Beijing China.

Bowu Zhang, Wei Cheng, Limin Sun, Xiuzhen Cheng, Taieb Znati, Mznah A. Al-Rodhaan, Abdullah Al-Dhelaan, “Queuing Modeling for Delay Analysis in Mission Oriented Sensor Networks under the Protocol Interference Model”, in ACM MiSeNet’13, October 4, 2013, Miami, Florida, USA. (Best Paper Award)

Wei Zhou, Tao Jing, Wei Cheng, Tao Chen, Yan Huo, “Combinatorial Auction Based Channel Allocation in Cognitive Radio Networks”, in CROWNCOM, July 8-10, 2013, Washington DC, USA.

Tao Jing, Xiaoshuang Xing, Wei Cheng, Yan Huo, Taieb Znati , “Cooperative Spectrum Prediction in Multi-PU Multi-SU Cognitive Radio Networks” in CROWNCOM, July 8-10, 2013, Washington DC, USA.

Xianfu Chen, Tao Chen, Wei Cheng, Honggang Zhang, “Reciprocity Inspired Learning for Opportunistic Spectrum Access in Cognitive Radio Networks,” in CROWNCOM, July 8-10, 2013, Washington DC, USA.

Wei Cheng, Kefeng Tan, Victor Omwando, Jindan Zhu, Prasant Mohapatra, “RSS-Ratio for Enhancing Performance of RSS-based Applications, in IEEE INFOCOM, April 2013, Turin, Italy.

Xinlei Wang, Wei Cheng, Prasant Mohapatra, Tarek Abdelzaher, “AnonyTrust: An Provenance-based Scheme towards Anonymous Trust in Participatory Sensing”, in IEEE INFOCOM, April 2013 , Turin, Italy.

Ningning Cheng, Xinlei Wang, Wei Cheng, Prasant Mohapatra, Aruna Seneviratne, “Characterizing Privacy Leakage of Public WiFi Networks for Users on Travel”, in IEEE INFOCOM, April 2013, Turin, Italy.

Strack B, Jacobs K and Cios KJ. 2013. Biological Restraint on the Izhikevich Neuron Model Essential for Seizure Modeling. Conf. Proceedings of the 6th November, 395-398; Student Best Paper Award

Strack B, Jacobs K and Cios KJ. 2013. Simulating Lesions in Multi-layer, Multi-columnar Model of Neocortex. Conf. Proceedings of the 6th Int. IEEE EMBS Conference on Neural Engineering, San Diego, 6-8 November, 835-838

Dinh TN, Nguyen NP, and Thai MT, An Adaptive Approximation Algorithm for Community Detection in Dynamic Scale-free Networks, in Proceedings of the 32nd IEEE Int. Conference on Computer Communications, (INFOCOM) Mini-Conference, Turin, Italy, 2013

Nguyen DT, Zhang H, Das S, Thai MT, and Dinh TN, Least Cost Influence in Multiplex Social Networks: Model Representation and Analysis, The IEEE International Conference on Data Mining (ICDM), Dallas, Dec. 2013

Zhang, Dinh TN, and Thai MT, Maximizing the Spread of Positive Influence in Online Social Networks, The 33rd IEEE International Conference on Distributed Computing Systems (ICDCS), Philadelphia, 2013

Carol Fungand Raouf Boutaba, "Design and Management of Collaborative Intrusion Detection Networks". The 15th IFIP/IEEE International Symposium on Integrated Network Management (IM 2013). Dissertation Paper. Ghent, Belgium, 2013. Best Dissertation Award

Nalluri, J, Kamapantula, B, Ghosh, P, Barh, D, Jain, N, Juneja, L, Barve, N. Determining miRNA-disease associations using bipartite graph modelling, ACM BCB 2013, pp 672-674.

Nazi, A, Raj, M, Francesco, M.D, Ghosh, P, Das, S.K. Robust Deployment of Wireless Sensor Networks using Gene Regulatory Networks, ICDCN 2013, pp. 192-207.

Abdelzaher, A, Kamapantula, B, Ghosh, P., and Das, S.K. A Theoretical Framework for Quantifying the Robustness of Biological Network Topologies, In proc. of Complex Network Dynamics Workshop (CoNeD 2013) in conjunction with ICDCN 2013, pp. 1-6.

Zigic Lj., Strack R., Kecman V., L2 Support Vector Machines Revisited - Novel Direct Learning Algorithm and Some Geometric Insights, Proc. of 19th 339, 2013

Test E., Zigic Lj., Kecman V., Feature Ranking Using Gini Index, Scatter Ratios, and Nonlinear SVM, Proc. of IEEE South-East Conf., Jacksonville, FL, April 4-7, 2013

Albarakati N., Kecman V., Fast Neural Network Algorithm For Solving Classification Tasks, Proc. of IEEE South-East Conf., Jacksonville, FL, April 4-7, 2013

Chung K, Katz J, Zhou H. Functional Encryption from (Small) Hardware Tokens. ASIACRYPT 2013, Bengaluru, India, December 1-5, 2013.

Katz J, Thiruvengadam A, Zhou H. Feasibility and Infeasibility of Adaptively Secure Fully Homomorphic Encryption. 16th International Conference on Practice and Theory in Public-Key Cryptography (PKC 2013), Nara, Japan, February 26 - March 1, 2013

Choi SG, Katz J, Wee H, Zhou H. Efficient, Adaptively Secure, and Composable Oblivious Transfer with a Single, Global CRS. 16th International Conference on Practice and Theory in Public-Key Cryptography (PKC 2013), Nara, Japan, February 26 - March 1, 2013

Fehr S, Katz J, Song F, Zhou H, Zikas V. Feasibility and Completeness of Cryptographic Tasks in the Quantum World. 10th Theory of Cryptography Conference (TCC 2013), Tokyo, Japan, March 3-6, 2013

Min Li, Wanyu Zang, Kun Bai, Meng Yu, Peng Liu. “MyCloud -- Supporting User-Configured Privacy Protection in Cloud Computing”. In Annual Computer Security Applications Conference. New Orleans, Louisiana USA, December 2013.

Carol Fung and Raouf Boutaba. "Intrusion Detection Networks: A Key to Distributed Security", CRC Press. 259 pages. ISBN: 978-1-4665-6412-1. November 2013.

Dinh TN, Thai MT, and Nguyen DT, A Unified Approach for Domination Problems on Different Network Topologies, Handbook of Combinatorial Optimization, (P. Pardalos, D. Du, and R. Graham eds), Springer Publisher, ISBN 978-1-4419-7996-4.Thai MT, Dinh TN, and Shen Y, Hardness and Approximation of Network Vulnerability, Handbook of Combinatorial Optimization, (P. Pardalos, D. Du, and R. Graham eds), Springer Publisher, ISBN 978-1-4419-7996-4.

USA 8,145,585 Issued on: March 27, 2012. Automated methods and systems for the detection and identification of money service business transactions.  Inventors:  Najarian, K., & Darvish, A.

Arodz, T.& Plonka, P.M. Effects of point mutations on protein structure are nonexponentially distributed. Proteins: Structure, Function and Bioinformatics, 80:1780-1790, Wiley, 012 http://dx.doi.org/10.1002/prot.24073, Impact Factor: 3.392.

Mayo, M., Abdelzaher, A.F., Perkins, E.J., & Ghosh, P. (2012) Motif participation by genes in E. coli transcriptional networks. Front. Physio. 3:357. doi: 10.3389/fphys.2012.00357.Hassan, S., Schneider, M.P., Ramos, R.T., Carneiro, A., Lima, A.R., Guimarães, L.C., Ali, A., Bakhtiar, S., Pereira, U., Santos, A., Soares, S.C., Dorella, F., Pinto, A., Ribeiro, D., Barbosa, M.S., Almeida, S., Abreu, V.A., Aburjaile, F., Fiaux, K.K., Barbosa, E.G., Diniz, C., Rocha, F., Saxena, R., Tiwari, S., Zambare, V., Ghosh, P., Pacheco, L.G., Dowson, C., Kumar, A., Barh, D., Miyoshi, A., Azevedo, V., & Silva, A. Whole-Genome Sequence of Corynebacterium pseudotuberculosis Strain 162, Isolated from Camel, J Bacteriol. 2012 Oct; 194(20):5718-9. Impact factor: 3.825.

Shandilya, S., Ward, K.,  Kurz, M., & Najarian, K. "Non-Linear Dynamical Signal Characterization for Prediction of Defibrillation Success through Machine Learning", BMC Medical Informatics and Decision Making 2012, 12:116 doi:10.1186/1472-6947-12-116.

Manjili, M., Najarian, K., & Wang,X-Y. "Signatures of the tumor-immune interactions as biomarkers for breast cancer prognosis", Vol. 8, No. 6, pp. 703-711, Future Oncology, June 2012.

Belle, A., Hobson-Hargraves, R., & Najarian, K. "An Automated Optimal Engagement and Attention Detection System Using Electrocardiogram," Computational and Mathematical Methods in Medicine, vol. 2012, Article ID 528781, 2012.

Davuluri, P., Wu, J., Tang, Y., Cockrell, C. H., Ward, K. R., Najarian, K., & Hobson-Hargraves, R. "Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries," Computational and Mathematical Methods in Medicine, vol. 2012, Article ID 898430, 2012.

Wu, J., Davuluri, P., Ward, K. R., Cockrell, C., Hobson, R. &  Najarian, K.  Fracture Detection in Traumatic Pelvic CT Images, International Journal of Biomedical Imaging, Volume 2012, Article ID 327198, pp. 1-10, 2012.

Silva A., Ramos, R., Carneiro, A., Almeida, S., Barbosa, S.,  Pinto, A.C., Cerdeira, L., Santos, A., Soares, S., Guimaraes, L., Barbosa, E., Figueira, F., Souza, F., Abreu, V.C., Dorella, F., Pacheco, L., Ghosh, P., Zambare, V., Barve, N., Tiwari, S., Barh, D., Miyoshi, A., Schneider, M.P., & Azevedo, V. Corynebacterium pseudotuberculosis 316, complete genome. GenBank: CP003077.1, 14-NOV-2012.

Silva, A., Cerdeira, L., Bol, E., Barbosa, M.S., Muller, B., Helden, P.V., Santos, A.R., Ramos, R.T.J., Carneiro, A. R., Guimaraes, L.C., Aburjaile, F. F., Padua, U.D., Arbosa, E., Fiaux, K.K.,  Diniz ,C.A.A., Soares, S.C., Pinto, A.C., Almeida, S.S., Abreu, V.A.C., Hassan, S.S., Khatri, G., Rahangdale S, Gupta K, Verma A, Ghosh P, Zambare V, Kumavath RN, Barh D, Miyoshi A, Schneider, M.P.C., & Azevedo, V. Corynebacterium pseudotuberculosis P54B96, complete genome. GenBank: CP003385.1, 23-MAR-2012.

Silva, A., Lopes, T., Ramos, R.T.J., Carneiro, A.R., Barbosa, M.S., Santos, A.R., Guimaraes, L.C., Aburjaile, F.F., Padua, U.D., Barbosa, E., Fiaux, K.K., Diniz, C.A., Soares, S.C., Pinto, A.C., Almeida, S.S., Abreu, V.A.C., Hassan, S.S., Khatri, G., Rahangdale, S., Gupta, K., Verma, A., Kumavath, R.N., Ghosh, P., Zambare, V., Barh, D., Miyoshi, A., Schneider, M.P.C., & Azevedo, V. Corynebacterium pseudotuberculosis 267, complete genome. GenBank: CP003407.1, 20-JUN-2012.

Silva, A., Saleh, M. , Selim, S.A., Cerdeira, L., Ramos, R.T., Carneiro, A.R., Barbosa, S., Santos, A., Soares, S., Guimaraes, L., Diniz, C.A., Fiaux, K., Hassan, S.S., Ali, A., Barbosa, E., Figueira, F., Pinto, A.C., Almeida, S., Abreu, V.C., Dorella, F., Pacheco, L., Souza, F., Ghosh, P., Zambare, V., Barh, D., Miyoshi, A., Schneider, M.P.,  & Azevedo, V.  Corynebacterium  pseudotuberculosis 31, complete genome. GenBank:  CP003421.1, 14-NOV-2012.

Silva, A., Ramos, R. , Carneiro, A. R. , Cerdeira, L. , Barbosa, S., Santos, A., Soares, S., Guimaraes, L., Diniz, C.A.A., Fiaux, K., Hassan, S.S., Ali, A., Barbosa, E., Figueira, F., Pinto, A.C., Almeida, S., Abreu, V.C., Dorella, F., Pacheco, L., Souza, F., Dowson, C.G., Ghosh, P., Zambare, V., Barh, D., Miyoshi, A., Schneider, M.P.,  Azevedo, V.  Corynebacterium pseudotuberculosis 258, complete genome. GenBank:  CP003540.1, 22-MAY-2012.

Silva, A., Ramos, R., Carneiro, A.R.,  Barbosa, S.,  Santos, A., Soares, S.,  Guimaraes, L.,  Diniz, C.A.A.,  Fiaux, K.,  Hassan, S.S., Ali, A.,  Barbosa, E.,  Figueira, F.,  Pinto, A.C., Almeida, S., Abreu, V.C.,  Dorella, F.,  Pacheco, L.,  Dowson, C.G.,  Souza, F., Ghosh, P.,  Zambare, V.,  Barh, D., Miyoshi, A.,  Schneider, M.P.,  Azevedo, V. Corynebacterium pseudotuberculosis Cp162, complete genome. GenBank:  CP003652.1, 28-SEP-2012.

Slawek, J., & Arodz, T. ADANET: Inferring Gene Regulatory Networks using Ensemble Classifiers.In: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB'12), ACM New York, NY, USA, 2012 Pages 434-441 http://dl.acm.org/citation.cfm?doid=2382936.2382992.

Gao, X.,& Arodz, T.  Robust differential co-expression discovery: an insight into pharmacodynamics of tyrosine kinase inhibitor In: Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB'12), ACM New York, NY, USA, 2012 Pages 604-606 http://dl.acm.org/citation.cfm?doid=2382936.2383037.

Chaitankar, V., Ghosh P., Elasri, M., Gust, K., & Perkins, E. Genome scale inference of transcriptional regulatory networks using mutual information on complex interactions, Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (BCB), 2012, pp. 643-648.

Chaitankar, V., Ghosh, P., Elasri, M., Gust, K., & Perkins, E. sCoIn: A Scoring algorithm based on COmplex INteractions for reverse engineering regulatory networks, Proceedings of the IEEE 12th International Conference on Bioinformatics and Bioengineering (BIBE), 2012, pp. 1-6.

Abdelzaher, A., Kamapantula, B., Ghosh, P., & Das, S.K. Empirical Prediction of Packet Transmission Efficiency in Bio-Inspired Wireless Sensor Networks, Proceedings of the 2012 IEEE 12th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 271-276.

Kamapantula, B., Abdelzaher, A., Ghosh, P., Mayo, M., Perkins, E., & Das, S.K. Performance of Wireless Sensor Topologies Inspired by E. coli Genetic Networks, Proceedings of 8th IEEE PerCom International Workshop on Sensor Networks and Systems for Pervasive Computing, PerSens 2012, pp. 302-307.

Ghosh, P., Datta, B., & Rangachari, V. Computational Predictions for the Nucleation Mass and Lag times Involved in Aβ42 Peptide Aggregation. Proceedings of the 3rd International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC Bioinformatics), 2012, pp. 312-316.

Salman, R., & Kecman, V. Regression as Classification, IEEE SouthEast Conference Paper, Session: F3-A: Data Mining and Machine Learning I, Orlando, FL, March 2012.

Test, E., Kecman, V., Strack, R., Li, Q., & Salman, R. Feature Ranking for Pattern Recognition: A Comparison of Filter Methods, IEEE SouthEast Conference Paper, Session: F4-A: Data Mining and Machine Learning II, Orlando, FL, March 2012.

Strack, R., & Kecman, V. Minimal Norm Support Vector Machines for Large Classification Tasks, Proc. of the 11^thIEEE international conference on machine learning applications (ICMLA 2012), Session 7, Boca Raton, FL, 2012.

Belle, A., Pfaffenberger, M.,  Hargraves, R. H.,  Najarian, K.‘An Automated Decision Making System for Detecting Loss of Attention In Individuals Using Real Time Processing of Electroencephalogram’, VII International Workshop on Biosignal Interpretation, Como, Italy, 2012.

Davuluri, P., Wu, J., Belle, A., Tang, Y., Cockrell, C., Ward, K., Hargraves, R., Najarian, K. ‘An Image Processing And Machine Learning Based Computer-Aided Decision Support For Traumatic Pelvic Injuries’, VII International Workshop on Biosignal Interpretation, Como, Italy, 2012.

Zhen, Y., Datta, B., Wang, A.H., Yu, M., & Zang, W. A Novel Spam Campaign in Online Social Networks. CoNeD 2013(workshop).

Liu, X., Wang, B., Yang, X., Yu, M. & Zang, W. Obtaining K-Obfuscation for Profile Privacy in Social Networks. The 7th International Conference on Frontier of Computer Science and Technology (FCST-12).

Gu, Q., Jones, K., Zang, W., Yu, M., & Liu, P. Revealing Abuses of Channel Assignment Protocols in Multi-Channel Wireless Networks: An Investigation Logic Approach. In the 17th European Symposium on Research in Computer Security (ESORICS 2012). Acceptance rate: 20%.

Li, M., Zhang, Y., Bai, K., Zang, W., Yu, M., & He, X. Improving Cloud Survivability through Dependency based Virtual Machine Placement (short paper). In the International Conference on Security and Cryptography (SECRYPT'12), Rome,Italy, 24-27 July 2012.

Gu, Q., Zang, W., Yu, M., & Liu, P. Collaborative Traffic-aware Intrusion Monitoring in Multi-channel Mesh Networks. In the 11th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom-2012), Liverpool, UK, 25-27 June 2012.

Zhang, Y., Li, M., Bai, K., Yu, M., & Zang, W. Incentive Compatible Moving Target Defense against VM-Colocation Attacks in Clouds. In IFIP International Information Security and Privacy Conference 2012, Heraklion, Crete, Greece, 4-6 June 2012. Acceptance rate: 25%.

Pan, W., Zhang, W., Yu, M., & Jing, J. Improving Virtualization Security by Splitting Hypervisor into Smaller Components. In The 26th Annual WG 11.3 Conference on Data and Applications Security and Privacy (DBSec'12), Institut Mines-Télécom, Paris, France. July 11-13, 2012.

Meredith, M.A., Cios, K.J., McQuiston, A.R., Lim, H.K., Keniston, L.P. & Clemo, H.R. 2012.  Neuroanatomical Identification of Multisensory Convergence on Higher-level Cortical Neurons. In: The New Handbook of Multisensory Processing, Barry Stein (ed.), 81-96, MIT Press.

Chaitankar, V., Barh, D., Zambare, V., Azevedo, V., & Ghosh, P. Computational Regulomics: Information Theoretic Approaches Towards Regulatory Network Inference. In “OMICS: Applications in Biomedical, Agricultural, and Environmental Sciences” ISBN 9781466562813. Edt by Barh D, Zambare V, Azevedo V. CRC Press, USA.

Barh, D., Yiannakopoulou, E.C., Salawu, E.O., Bhattacharjee, A., Chowbina, S., Ghosh, P., &Azevedo, V.: In silico Disease Models, In “Animal Biotechnology: Models in Discovery and Translation”, ISBN: 9780124160026, Edt by Verma and Singh. Elsevier, USA.

Najarian, K. Methods and Systems for Analysis of Dynamic Biological Pathways, US. Patent 8,065,089, Nov. 22, 2011.

Czech, W., Dzwinel, W., Goryczka, S., Arodz, T. and Dudek, A.Z. 2011. Exploring Complex Networks with Graph Investigator Research Application. Computing & Informatics, 30:381-410.

Lim, H.K., Keniston, L.P., Shin, J.H., Allman, B.L., Meredith, M.A. and Cios, K.J. 2011. Connectional Parameters Determine Multisensory Processing in a Spiking Network Model of Multisensory Convergence. Experimental Brain Research, 213(2-3):329-339.

Nguyen, C., Gardiner, K. and Cios, K.J. 2011. Protein Annotation from Protein Interaction Networks and Gene Ontology. Journal of Biomedical Informatics, 44(5):824-829.

Lim, H.K., Keniston, L.P. and Cios, K.J. 2011. Modeling of Multisensory Convergence with a Network of Spiking Neurons: A Reverse Engineering Approach. IEEE Transactions on Biomedical Engineering, 58(7):1940-1949.

Nguyen, D., Costa, A., Cios, K.J. and Gardiner, K. 2011. Machine Learning Methods Predict Locomotor Response to MK-801 in Mouse Models of Down Syndrome. Journal of Neurogenetics, 25(1-2):40-51.

Achuthan, S., Chung, B.J., Ghosh, P., Rangachari, V. and Vaidya, A. 2011. A Modified Stokes Einstein Equation for Aβ Aggregation. BMC Bioinformatics, 12(Suppl. 10):S13: 1-13.

Mayo, M., Perkins, E. and Ghosh, P. 2011. First-Passage Time Analysis of a One-Dimensional Diffusion-Reaction Model: Application to Protein Transport along DNA. BMC Bioinformatics, 12(Suppl. 10):S18: 1-14.

Ghosh, S., Ghosh, P., Basu, K. and Das, S. 2011. A Discrete Event-Based Stochastic Simulation Platform for ‘in Silico’ Study of Molecular Level Cellular Dynamics. Journal of Biotechnology and Biomaterials, 1(5):1-19.

Cerdeira, L.T., Schneider, M.P., Pinto, A.C., de Almeida, S.S., Dos Santos, A.R., Barbosa, E.G., Ali, A., Aburjaile, F.F., de Abreu, V.A., Guimarães, L.C., Soares Sde, C., Dorella, F.A., Rocha, F.S., Bol, E., Gomes de Sá, P.H., Lopes, T.S., Barbosa, M.S., Carneiro, A.R., Jucá Ramos, R.T., Coimbra, N.A., Lima, A.R., Barh, D., Jain, N., Tiwari, S., Raja, R., Zambare, V., Ghosh, P., Trost, E., Tauch, A., Miyoshi, A., Azevedo, V. and Silva, A. Dec. 2011. Complete Genome Sequence of Corynebacterium pseudotuberculosis Strain CIP 52.97, Isolated from a Horse in Kenya. J Bacteriol; 193(24):7025-6.

Salman, R., Kecman, V., Li, Q., Strack, R. and Test, E. 2011. Fast K-Means Algorithm Clustering. International Journal of Computer Networks & Communications (IJCNC), 3(4): 17-31.

Yang, T., Kecman, V., Cao, L.-B., Zhang, C.-Q. 2011. Margin-Based Ensemble Classifier for Protein Fold Recognition. Expert Systems with Applications, Elsevier, 38(10): 12, 348-12, 355.

Li Q., Salman R., Test E., Strack R., Kecman V., GPUSVM: A Comprehensive CUDA Based Support Vector Machine Package, Cent. Eur. J. Comp. Sci., 1(4), pp. 387-405, 2011

Rodríguez, J.T., Vitoriano, B., Montero, J., Kecman, V. 2011. A Disaster-Severity Assessment DSS Comparative Analysis. OR Spectrum, Springer-Verlag, 33(3): 451-479.

Mirshahi, N., Demir, S.U., Ward, K., Hobson, R., Hakimzadeh, R. and Najarian, K. 2011. An Adaptive Entropic Thresholding Technique for Image Processing and Diagnostic Analysis of Microcirculation Videos. International Journal on Advances in Life Sciences, 2(3-4): 133-142.

Liu, P. and Yu, M. Jan. 2011. Damage Assessment and Repair in Attack-Resilient Distributed Database Systems. Computer Standards and Interfaces, 33:96-107.

Cerdeira, L., Schneider, M.P.C., Barbosa, M.S., Ramos, R.T.J., Carneiro, A.R., Santos, R.S., Lima, M., DAFonseca, V., Almeida, S.S., Santos, A.R., Soares, S.C., Pinto, A.C., Ali, A., Barbosa, E., Dorella, F.A., Rocha, F.S., Guimaraes, L.G., Belchior, S.B., Ghosh, P., Zambare, V., Barve, N., Tiwari, S., Barh, D., Miyoshi, A. and Azevedo, V. Corynebacterium pseudotuberculosis PAT10, complete genome. [July 18, 2011] GenBank: CP002924.1

Nguyen, D., Dzwinel, W. and Cios, K.J. Visualization of Highly-Dimensional Data in 3D Space. 11th Int. Conf. on Intelligent Systems Design and Applications (ISDA 2011), Nov. 22-24, 2011, Cordoba, Spain: 225-230.

Mayo, M., Perkins, E. and Ghosh, P. Downstream Exploration of DNA-Bound Searching Proteins: a Diffusion-Reaction Model. IEEE 11th International Conference on Bioinformatics & Bioengineering BIBE 2011: 21-26.

Chaitankar, V., Ghosh, P. and Perkins, E. S-REVEAL: A Scalable implementation of REVEAL for Gene Regulatory Network Reconstruction. IEEE ISDA 2011: 1-6.

Chaitankar, V., Ghosh P., Elasri, M. and Perkins, E. A Scalable Gene Regulatory Network Reconstruction Algorithm Combining Gene Knock-Out Data. Third International Conference on Bioinformatics and Computational Biology, BiCob 2011: 74-79.

Ghosh, P., Mayo, M., Chaitankar, V., Habib, T., Perkins, E. and Das, S.K. Principles of Genomic Robustness Inspire Fault-Tolerant WSN Topologies: A Network Science-Based Case Study. The Seventh IEEE PerCom International Workshop on Sensor Networks and Systems for Pervasive Computing, PerSens 2011: 160-165.

Chen, W., Ward, K., Li, Q., Kecman, V., Najarian, K. and Menke, N. Agent-Based Modeling of Blood Coagulation System: Implementation Using a GPU-Based High Speed Framework. IEEE EMBC11 2011, Simulation, Boston: 145-148.

Salman, R., Kecman, V., Li, Q., Strack, R. and Test, E. Two-Stage Clustering with K-Means Algorithm. In A. Özcan, J. Zizka and D. Nagamalai (Eds.): Communications in Computer and Information Science, 1, Volume 162, Recent Trends in Wireless and Mobile Networks, Part 1,Springer-Verlag, 2011, Berlin, Heidelberg: 110-122.

Salman, R. and Kecman, V. The Effect of Cluster Location and Dataset Size on 2-Stage K-Means Algorithm. 10th International Workshop on Electronics, Control, Measurement and Signals, 10.1109/ IWECMS.2011.5952377, 2011, Liberec, Czech Republic: 1-5.

Belle, A., Hobson, R. and Najarian, K. A Physiological Signal Processing System for Optimal Engagement and Attention Detection. 2011 International Workshop on Biomedical and Health Informatics, part of IEEE International Conference Bioinformatics & Biomedicine, Nov. 12-15, 2011, Atlanta.

Ansari, S., Belle, A., Hobson, R., Ward, K. and Najarian, K. Reduction of Periodic Motion Artifacts from Impedance Plethysmography. 2011 International Workshop on Biomedical and Health Informatics, part of IEEE International Conference Bioinformatics & Biomedicine, Nov. 12-15, 2011, Atlanta.

Wu, J., Davuluri, P., Belle, A., Cockrell, C., Tang, Y., Ward, K., Hobson, R. and Najarian, K. Fracture Detection and Quantitative Measure of Displacement in Pelvic CT Images. 2011 International Workshop on Biomedical and Health Informatics, part of IEEE International Conference Bioinformatics & Biomedicine, Nov. 12-15, 2011, Atlanta.

Davuluri, P., Belle, A., Cockrell, C., Tang, Y., Ward, Najarian, K. and Hargraves, R. A Hybrid Approach for Hemorrhage Segmentation in Pelvic CT Scans. 2011 International Workshop on Biomedical and Health Informatics, part of IEEE International Conference Bioinformatics & Biomedicine, Nov. 12-15, 2011, Atlanta.

Shandilya, S., Ward, K., Kurz, M. and Najarian, K. Predicting Defibrillation Success with a Multiple-Domain Model Using Machine Learning. 2011 IEEE International Conference on Complex Medical Engineering(CME 2011), May 22-25, 2011, Harbin, Heilongjiang, China: 9-14.

Ansari, S., Ward, K. and Najarian, K. A New Method for Motion Artifact Reduction. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society(EMBC '11), 2011, Boston.

Chen, W., Menke, N., Li, Q., Kecman, V. and Najarian, K. Modeling of Blood Coagulation System: Implementation Using a GPU-Based High Speed Framework. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), 2011, Boston.

Wu, J., Davuluri, P., Hobson, R., Cockrell, C., Ward, K. and Najarian, K. A New Hierarchical Method for Multi-Level Segmentation of Bone in Pelvic CT Scans. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), 2011, Boston.

Luo, Y., Bsoul, R., Ward, K. and Najarian, K. Confidence-Based Classification with Dynamic Conformal Prediction and Its Applications in Biomedicine. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), 2011, Boston.

Davuluri, P., Wu, J., Hobson, R., Cockrell, C., Ward, K. and Najarian, K. An Automated Method for Hemorrhage Detection in Traumatic Pelvic Injuries. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC '11), 2011, Boston.

Gu, Q., Yu, M., Zang, W. and Liu, P. Lightweight Attacks Against Channel Assignment Protocols in Mimc Wireless Networks. IEEE ICC, Communication and Information System Security Symposium, June 5-9, 2011, Kyoto, Japan: 1-6.

Pan, W., Jing, J., Xia, L., Liu, Z. and Yu, M. An Efficient RSA Implementation Without Precomputation. 7th International Conference on Information Security and Cryptology (INSCRYPT) 2011. Nov. 30-Dec. 3, 2011, Beijing.

Chaitankar, V., Zhang, C., Ghosh, P., Perkins, E., Gong, P. and Deng, Y. 2011. Predictive Minimum Description Length Principle Approach to Infer Gene Regulatory Networks. Springer Advances in Experimental Medicine and Biology,696:37-43.

Shin, J.H., Smith, D., Swiercz, W., Staley, K., Rickard, T., Montero, J., Kurgan, L. and Cios, K. 2010. Recognition of Partially Occluded and Rotated Images with a Network of Spiking Neurons. IEEE Transactions on Neural Networks, 21(11):1697-1708.

Yang, T., Kecman, V., Cao, L.-B. 2010. Classification by ALH-Fast Algorithm. Tsinghua Science & Technology, 15(3): 275-280.

Kao, J. W.-H., Berber, S. M. and Kecman, V. 2010. Blind Multiuser Detector for Chaos-Based CDMA Using Support Vector Machine. IEEE Transactions on Neural Networks, 21(8): 1221-1231.

Leonhardt, S., Ahrens, P. and Kecman, V. 2010. Analysis of Tidal Breathing Flow Volume Loops for Automated Lung Function Diagnosis in Infants, IEEE Transactions on Biomedical Engineering, 57(8): 1945-1953.

Mijailovich, S.M., Li, X.-C., del Álamoa, J.C., Griffiths, H., Kecman, V. and Geeves, M.A. 2010. Resolution and Uniqueness of Estimated Parameters of a Model of Thin Filament Regulation in Solution. Computational Biology and Chemistry,34: 19-33.

Yang, T. and Kecman, V. 2010. Face Recognition with Adaptive Local Hyperplane Algorithm. Pattern Analysis & Applications, Springer-Verlag, 13(1): 79-83.

Vasilache, S., Mirshahi, N., Ji, S.Y., Mottonen, J., Jacobs, D.J. and Najarian, K. 2010. A Signal Processing Method to Explore Similarity in Protein Flexibility. Advances in Bioinformatics, vol. 2010, Article ID 454671, doi:10.1155/2010/454671.

Nguyen, C.D., Gardiner, K.J., Nguyen, D., Costa, A. and Cios, K. miDivCon: Framework and Method for Multiple Instance Learning. Tenth International Conference on Intelligent Systems Design and Applications (ISDA 2010), Nov. 29-Dec. 1, 2010, Cairo: 495-500.

Lovelace, J., Rickard, T. and Cios, K. A Spiking Neural Network Alternative for the Analog to Digital Converter. International Joint Conference on Neural Networks at WCCI 2010, Barcelona, Spain, July 18-23, 2010. IEEE: New York, 463-470.

Lim, H.K., Keniston, L.P., Shin, J.H., Nguyen, C.D., Meredith, M.A. and Cios, K. A Neuronal Multisensory Processing Simulator, International Joint Conference on Neural Networks at WCCI 2010, Barcelona, Spain, July 18-23, 2010, IEEE: New York: 281-287

Li, Q., Kecman, V. and Salman, R. A Chunking Method for Euclidean Distance Matrix Calculation on Large Dataset Using Multi-GPU. IEEE’s ICMLA 2010 Conference, Dec. 12-14, 2010, Washington, D.C.

Kao, J.W.H., Berber, S.M. and Kecman, V. Adaptive Multi-Code Chaos-Based CDMA with Unequal Error Protection using Reduced Support Vector Machine. IEEE Global Communication Conference, GLOBECOM 2010, Dec. 6-10, 2010, Miami.

Li, Q., Salman, R. and Kecman, V. An Intelligent System for Accelerating Parallel SVM Classification Problems on Large Datasets Using GPU. IEEE’s ISDA conference 2010, Cairo.

Kao, J.W.H., Berber, S.M. and Kecman, V. Practical Training Data for Support Vector Machine Receiver in a Chaos-Based CDMA. 16th Asia-Pacific Conference on Communications 2010, Oct. 31-Nov. 3, 2010, Auckland, New Zealand.

Li, Q., Salman, R. and Kecman, V. Accelerating Weighted Euclidean Distance and Cosine Similarity Calculation Using GPU. IEEE’s IITA conference 2010, Qinhuangdao, China.

Kao, J.W.H., Berber, S.M. and Kecman, V. Reduced Support Vector Machine Detector for Chaos-Based CDMA Systems. 2010 International Symposium on Spread Spectrum Techniques and Applications 2010, Taichung, Taiwan: 215-220.

Kecman, V. and Brooks, J.P. Locally Linear Support Vector Machines and Other Local Models. WCCI 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain: 2615-2620.

Vance, T., Reljin, N., Lazarevic, A., Pokrajac, D., Kecman, V., Melikech, N., Marcano, A., Markushin, Y. and McDaniel, S. Classification of LIBS Protein Spectra Using Support Vector Machines and Adaptive Local Hyperplanes, WCCI 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain: 1207-1213.

Yang, T., Kecman, V., Cao, L. and Zhang, C. Testing Adaptive Local Hyperplane for Multi-Class Classification by Double Cross-Validation. 2010 IEEE World Congress on Computational Intelligence, Barcelona, Spain: 3895-3899.

Kecman, V. and Kikec, M. Erythemato-Squamous Diseases Diagnosis by Support Vector Machines and RBF NN, L. Rutkowski et al. (Eds.). ICAISC 2010, Part I, Lecture Notes in Computer Science, Artificial Intelligence and Soft Computing: 613-620.

Yang, T., Kecman, V., Cao, L. and Zhang, C. Combining Support Vector Machines and the T-Statistic for Gene Selection in DNA Microarray Data Analysis. In M.J. Zaki et al. (Eds.) PAKDD 2010, Part II, LNAI 6119, Springer-Verlag, Berlin, Heidelberg: 55-62.

Chen, W., Cockrell, C., Ward, K. and Najarian, K. Intracranial Pressure Level Prediction in Traumatic Brain Injury by Extracting Features from Multiple Sources and Using Machine Learning Methods. IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Ansari, S., Ward, K. and Najarian K. Adaptive Set-Membership Normalized Least Mean Squares: An Adaptive Filter for the Systems with Bounded Noise. Workshop on Mining and Management of Biological and Health Data, part of the 2010 IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Shandilya, S., Ward, K. and Najarian, K. A Time-Series Approach for Shock Outcome Prediction Using Machine Learning. First Workshop on Knowledge Engineering, Discovery and Dissemination in Health, part of the 2010 IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Bsoul, A.A.R., Ji, S.Y., Ward, K. and Najarian, K. A Unified Signal Processing and Machine Learning Method for Detection of Abnormal Heart Beats Using Electrocardiogram. First Workshop on Knowledge Engineering, Discovery and Dissemination in Health, part of the 2010 IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Ansari, S., Belle, A., Ward, K. and Najarian, K. Impedance Plethysmography on the Arms: Respiration Monitoring. First Workshop on Knowledge Engineering, Discovery and Dissemination in Health, part of the 2010 IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Vasilache, S., Smith, R., Wu, J., Davuluri, P., Ha, J., Ward, K., Cockrell, C. and Najarian, K. Predicting Pelvic Trauma Severity Using Features Extracted from Records and X-Ray and CT Images. First Workshop on Knowledge Engineering, Discovery and Dissemination in Health, part of the 2010 IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010), Dec. 18-21, 2010, Hong Kong.

Smith, R., Ward, K., Cockrell, C., Ha, J. and Najarian K. Detection of Fracture and Quantitative Assessment of Displacement Measures in Pelvic X-ray Images. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), March 14-19, 2010, Dallas.

Belle, A., Ji, S.Y., Ansari, S., Hakimzadeh, R., Ward, K. and Najarian, K. Frustration Detection with Electroencephalogram Signal using Wavelet Transform, Second International Conference on Advances in Biotechnologies (BIOTECHNO 2010), March 7-13, 2010, Cancun, Mexico.

Mirshahi, N., Demir, S.U., Ward, K., Hobson, R., Hakimzadeh, R. and Najarian, K. A Multi-Resolution Entropic-Based Image Processing Technique for Diagnostic Analysis of Microcirculation Videos. Second International Conference on Advances in Biotechnologies (BIOTECHNO 2010), March 7-13, 2010, Cancun, Mexico.

Demir, S., Mirshahi, N., Ward, K., Hobson, R.S., Hakimzadeh, R. and Najarian, K. Vessel Extraction of Microcirculatory Video Recordings Using Multi-Thresholding Based Verification Algorithm. Second International Conference on Advances in Biotechnologies (BIOTECHNO 2010), March 7-13, 2010, Cancun, Mexico.

Yu, M., Hai, W., Zang, W. and Peng, L. Evaluating Survivability and Costs of Three Virtual Machine-Based Server Architectures, SECRYPT 2010,Article No. 134, July 2010, Seville, Spain.

Heywoong, K., Qijun, Q., Yu, M., Zang, W. and Peng, L. Simulation Framework for Performance Analysis of Multi-Interface and Multi-Channel Wireless Networks in INET/OMNET++. Communications and Networking Simulation Symposium 2010 (CNS 2010), Article No. 101, Orlando, Fla.

Yang, T. and Kecman, V. 2010. Machine Learning by Adaptive Local Hyperplane Algorithm: Theory and Applications, VDM-Verlag, Saarbrücken, Germany.

Gu, Q., Zang, W. and Yu, M., eds. 2010. ICST International Workshop on Security in Emerging Wireless Communication and Networking Systems, Springer.

Cios, K. and Kurgan, L.A. 2010. Machine Learning Algorithms Inspired by Work of Ryszard Spencer Michalski. In J. Koronacki et al. (Eds.) Advances in Machine Learning I, SCI 262, Springer: 49-74.

Murrill, B.W. 2010. Fault-Based Testing, Encyclopedia of Software Engineering, 1(1): 300-307.

Najarian, K. and Vasiliache, S. 2010. Probably Approximately Correct Theory, Statistical Learning Theory. In N.M. Seel (Ed.): Encyclopedia of the Science of Learning, Springer.

Yang, T. and Kecman, V. 2009. Adaptive Local Hyperplane Algorithm for Learning Small Medical Data Sets, Expert Systems. The Journal of Knowledge Engineering, Wiley Interscience, Blackwell Publishing, 26(4): 355-359.

Murphy, R.B., Young, B.R. and Kecman, V. 2009. Optimising Operation of a Biological Wastewater Treatment Application. ISA Transactions,48: 93-97.

Ji, S.Y., Ward, K., Ryan, K., Rickards, C., Convertino, V., Vyas, N., Stivoric, J. and Najarian, K. 2009. Prediction of Hypovolemia Severity Using ECG Signal with Wavelet Transformation Analysis from a Mobile Armband. Circulation, 120:S1441.

Ji, S.Y., Bsoul, A.A.R., Ward, K., Ryan, K., Rickards, C., Convertino, V. and Najarian, K. 2009. Incorporating Physiological Signals to Blood Loss Prediction Based on Discrete Wavelet Transformation. Circulation, 120:S1483.

Bsoul, A.A.R., Ji, S.Y.,Ward, K., Ryan, K., Rickards, C., Convertino, V. and Najarian, K. 2009. Prediction of Severity of Blood Volume Loss Using Features Based on P, T and QRS Waves. Circulation, 120:S1466.

Ward, K., Vyas, N., Ji, S.Y., Rickards, C., Ryan, K., Convertino, V., Jackson, R. and Najarian, K. 2009. Use of Low-Level Physiologic Signals and Machine Learning to Derive Important Homodynamic Variables during Acute Volume Loss. Circulation, 120:S1482-S1483.

Demir, S., Mirshahi, N., Ward, K., Hobson, R. and Najarian, K. 2009. Vessel Segmentation Based on Multi-Thresholding for Diagnostic Analysis of Microcirculation. Circulation, 120:S1491.

Ji, S.Y., Ward, K. and Najarian, K. Nov. 2009. Brain Mapping and Detection of Functional Patterns in fMRI Using Wavelet Transform; Application in Detection of Dyslexia. BMC Medical Informatics and Decision Making, 9: (Suppl. 1):S6.

Chen, W., Smith, R., Ji, S.Y., Ward, K. and Najarian, K. Nov. 2009. Automated Ventricular Systems Segmentation in Brain CT Images by Combining Low-Level Segmentation and High-level Template Matching. BMC Medical Informatics and Decision Making,9 (Suppl. 1):S4.

Vasilache, S., Ward, K. and Najarian, K. Nov. 2009. Unified Wavelet and Gaussian Filtering for Segmentation of CT Images; Application in Segmentation of Bone in Pelvic CT Images. BMC Medical Informatics and Decision Making, 9 (Suppl. 1):S8.

Smith, R. and Najarian, K. 2009. A Hierarchical Method Based on Active Shape Models and Directed Hough Transform for Segmentation of Noisy Biomedical Images; Application in Segmentation of Pelvic X-ray Images. BMC Medical Informatics and Decision Making, 9 (Suppl. 1):S2.

Ji, S.Y., Smith, R., Huynh, T. and Najarian, K. 2009. A Comparative Analysis of Multi-Level Computer-Assisted Decision Making Systems for Traumatic Brain Injuries. BMC Medical Informatics and Decision Making, 9(2).

Choi, H., Wang, J. and Hughes, E. Scheduling for Inform Gathering on Sensor Network. ACM Journal of Wireless Networks, Jan. 2009, 15(1).

Shin, J-H., Smith, D. Swiniarski, R., Dudek, E., White, A., Staley, K. and Cios, K. Analysis of EEG Epileptic Signals with Rough Sets and SVMs. AIME'09 (Artificial Intelligence in Medicine 2009), July 18-22, 2009, Verona, Italy: 325-334.

Thaicharoen, S., Altman, T., Gardiner, K. and Cios, K. Discovering Relational Knowledge from Two Disjoint Sets of Literatures Using Inductive Logic Programming. IEEE Symposium on Computational Intelligence and Data Mining (IEEE CIDM 2009), March 30-April 2, 2009, Nashville, Tenn.: 283-290.

Kecman, V. and Yang, T. Adaptive Local Hyperplane for Regression Tasks. IEEE International Joint Conference on Neural Networks, June 14-19, 2009, Atlanta.: 1566-1570.

Kecman, V. and Yang, T. Protein Fold Recognition with Adaptive Local Hyperplane Algorithm. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2009), March 31-April 2, 2009, Nashville, Tenn.: 75-78.

Kecman, V. and Brooks, P.J. Locally Linear Support Vector Machines. INFORMS Annual Meeting, TA04, Joint Session ICS/DM Optimization in Data Mining/Machine Learning, presenter P.J. Brooks, Oct. 10-14, 2009, San Diego.

Ansari, S., Najarian, K., Ward, K. and Tiba, M.H. Extraction of Respiratory Rate from Impedance Signal Measured on Arm: A Portable Respiratory Rate Measurement Device. 2009 IEEE Conference on Bioinformatics and Biomedicine (IEEE BIBM 2009), Nov. 2009: 197-202.

Chen, W., Smith, R., Vasilache, S., Najarian, K., Ward, K., Cockrell, C. and Ha, J. Traumatic Pelvic Injury Outcome Prediction by Extracting Features from Relevant Medical Records and X-ray Images. 2009 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2009), Nov. 2009: 291-294.

Vasilache, S., Chen, W., Ward, K. and Najarian, K. Hierarchical Object Recognition in Pelvic CT Images. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), Sept. 3-6, 2009: 3533-3536.

Najarian, K., Hakimzadeh, R., Ward, K., Daneshvar, K. and Ji, S.Y. Combining Predictive Capabilities of Transcranial Doppler with Electrocardiogram to Predict Hemorrhagic Shock. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2009), Sept. 3-6, 2009: 2621-2624.

Hakimzadeh, R., Ji, S.Y., Smith, R., Ward, K., Daneshvar, K. and Najarian, K. Processing of Transcranial Doppler for Assessment of Blood Volume Loss. 2009 IEEE International Conference on Information Reuse & Integration (IRI '09), Aug. 10-12, 2009: 6-10.

Bsoul, A.A.R., Ji, S.Y., Ward, K. and Najarian, K. Detection of P, QRS, and T Components of ECG Using Wavelet Transformation. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-6.

Ji, S.Y., Chen, W., Ward, K., Rickard, C., Ryan, K., Convertino, V. and Najarian, K. Wavelet-Based Analysis of Physiological Signals for Prediction of Severity of Hemorrhagic Shock. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-6.

Chen, W. and Najarian, K. Segmentation of Ventricles in Brain CT Images Using Gaussian Mixture Model Method. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-6.

Demir, S., Mirshahi, N., Tiba, H., Draucker, G., Ward, K., Hobson, R. and Najarian, K. Image Processing and Machine Learning for Diagnostic Analysis of Microcirculation. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-5.

Vasilache, S. and Najarian, K. A Unified Method Based on Wavelet Filtering and Active Contour Models for Segmentation of Pelvic CT Images. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-5.

Smith, R. and Najarian, K. Splines and Active Model for Segmentation of Pelvic X-ray Images. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-6.

Olsen, G., Brilliant, S., Primeaux, D. and Najarian, K. An Image-Processing Enabled Dental Caries Detection System. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-8.

Olsen, G., Brilliant, S., Primeaux, D. and Najarian, K. Signal Processing and Machine Learning for Real-Time Classification of Ergonomic Posture with Unobtrusive On-Body Sensors; Application in Dental Practice. ICME International Conference on Complex Medical Engineering (CME 2009), April 9-11, 2009: 1-11.

Wang, J., Choi, H. and Jung, C. A Distributed Wireless Channel Assignment Algorithm with Collision Reduction. International Symposium on Collaborative Technologies and Systems (CTS 2009), Baltimore.

Gajic Z., M. Lim, D. Skataric, W. Su, V. Kecman, Optimal Control of Weakly Coupled Systems and Applications, CRC Press (Francis and Taylor), 2009

Gajic Z., M. Lim, D. Skataric, W. Su, V. Kecman, Optimal Control of Weakly Coupled Systems and Applications, Heritage Publishers, (Special Indian Edition), CRC Press (Francis and Taylor), 2009

Choi, H., Wang, J. and Hughes, E. Jan. 2009. Scheduling for Information Gathering on Sensor Network. ACM Journal of Wireless Networks, 15: 127-140.

Yang, S., Kim, Y. and Choi, H. April 2008. Vehicle Identification using Discrete Spectrums in Wireless Sensor Networks. Journal of Networks, 3(4): 51-63.

Kurgan, L., Cios, K., Zhang, H., Zhang, T., Chen, K., Shen, S. and Ruan, J. 2008. Sequence-based Methods for Real Value Predictions of Protein Structure. Current Bioinformatics, 3(3): 183-196.

Gehrke, A., Sun, S., Kurgan, L., Ahn, N., Resing, K., Kafadar, K. and Cios, K. 2008. Improved Machine Learning Method for Analysis of Gas Phase Chemistry of Peptides. BMC Bioinformatics, 9: 515.

Yen, C-Y and Cios, K. 2008. Image Recognition System Based on Novel Measures of Image Similarity and Cluster Validity. Neurocomputing, 72: 401-412.

Nguyen, C. and Cios, K. 2008. GAKREM: A Novel Hybrid Clustering Algorithm. Information Sciences, 178: 4205-4227.

Nguyen, C., Mannino, M., Gardiner, K. and Cios, K. 2008. ClusFCM: Algorithm for Prediction of Protein Functions Using Homologies and Protein Interactions. Journal of Bioinformatics and Computational Biology, 6(1): 203-222.

Kurgan, L., Cios, K. and Chen, K. 2008. SCPRED: Accurate Prediction of Protein Structural Class for Sequences of Twilight-Zone Similarity with Predicting Sequences. BMC Bioinformatics, 9: 226.

Chiua, R.W.K., Chana, K.C.A., Gao, Y., Laua, V.Y.M., Zhenga, W., Leunge, T.Y., Foof, C.H.F., Xiec, B., Tsuia, N.B.Y, Lun, F.M.F., Zeef, B.C.Y., Laue, T.K., Cantorg, C.R. and Loa, Y.M.D. Dec. 23, 2008. Noninvasive Prenatal Diagnosis of Fetal Chromosomal Aneuploidy by Massively Parallel Genomic Sequencing of DNA in Maternal Plasma. PNAS, 105(51): 20458-20463.

Valentea, A.X.C.N., Roberts, S.B., Buck, G.A. and Gao, Y. 2008. Functional Organization of the Yeast Proteome by a Yeast Interactome Map. PNAS Early Edition: 1-6.

Yang, T. and Kecman, V. 2008. Adaptive Local Hyperplane Classification. Neurocomputing,71: 3001-3004.

Murrill, B.W. Feb. 2008. An Empirical, Path-oriented Approach to Software Analysis and Testing. Journal of Systems and Software, 81(2): 249-261.

Jeong, D.H., Darvish, A., Najarian, K., Yang, J. and Ribarsky, W. Jan. 2008. Interactive Visual Analysis of Time-Series Microarray Data. Visual Computer, 24(12): 1053-1066.

Najarian, K., DeMott II, R. and Cooper, J. 2008. Automatic Target Recognition and Classification in Aerial Photography. International Journal of Systems Signal Control and Engineering Application, 1(1): 1-14.

Wang, J. and Choi, H. Dec. 2008. Efficient Power Allocation for Multi-User OFDM System. GESTS Transactions on Computer Science and Engineering, 51(1).

Wang, J., Masilela, M. and Liu, J. April 2008. Transmission Buffer Management and Node Failure Recovery in Wireless Sensor Networks. Mediterranean Journal of Computers and Networks, 4(2): 44-53.

Wang, J. and Liu, J. Feb. 29, 2008. Uplink Relaying in Hybrid Wireless Networks with Interference Reduction. ACM Journal of Wireless Networks, ISSN 1022-0038 (print), 1572-8196 (online).

Nguyen, C., Gardiner, K., Nguyen, D. and Cios, K. Prediction of Protein Functions from Protein Interaction Networks: A Naïve Bayes Approach. Pacific Rim International Conference on Artificial Intelligence, Dec. 15-19, 2008, Hanoi, Vietnam: 788-798.

Thaichareon, S., Altman, T. and Cios, K. Structure-Based Document Model with Discrete Wavelet Transforms and Its Application to Document Classification. 7th Australasian Data Mining Conference,Nov. 2008, Glenelg, Australia, 87: 209-217.

Yang, T. and Kecman, V. Classification by ALH-Fast Algorithm. Fifth International Symposium on Neural Networks (ISNN 2008), Sept. 24-28, 2008, Beijing, China.

Chen, G., Warren, J., Yang, T. and Kecman, V. Adaptive K-Local Hyperplane (AKLH) Classifiers on Semantic Spaces to Determine Health Consumer Webpage Metadata. 21th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS 2008), Jyväskylä, Finland: 287-289.

Kao, J., Berber, S. and Kecman, V. Blind Multi-user Detection of a Chaos-based CDMA System Using Support Vector Machines. 10th International Symposium on Spread Spectrum Techniques and Applications 2008, Bologna, Italy.

Ji, Y., Smith, R., Huynh, T. and Najarian, K. A Comparative Analysis of Multi-level Computer-Assisted Decision Making Systems for Traumatic Brain Injuries. BMC Medical Informatics and Decision Making, 9:2.

Najarian, K., DeMott II, R. and Cooper, J. Automatic Target Recognition and Classification in Aerial Photography. International Journal of Systems Signal Control and Engineering Applications 2008, 1(1): 1-14.

Ji, S.Y., Ward, K., Ryan, K., Rickard, C., Convertino, V. and Najarian, K. Heart Rate Variability Analysis Using Wavelet Transform to Predict Severity of Hemorrhagic Shock. American Heart Association (AHA) Resuscitation Science Symposium, Nov. 2008, New Orleans: 93.

Ji, S.Y. and Najarian, K. A Modified Maximum Correlation Modeling Method for fMRI Brain. IEEE Bioinformatics and Biomedicine (BIBM), International Workshop on Biomedical and Hearth Informatics (BHI), Nov. 3-5, 2008, Philadelphia: 64-49.

Chen, W., Smith, R., Ji, S.Y. and Najarian, K. Automated Segmentation of Lateral Ventricles in Brain CT Images. IEEE Bioinformatics and Biomedicine (BIBM), International Workshop on Biomedical and Hearth Informatics (BHI), Nov. 3-5, 2008, Philadelphia: 48-55.

Vasilache, S., Smith, R., Ji, S.Y., Najarian, K. and Huynh, T. Outcome Prediction in Traumatic Pelvic Injuries Using Maximum Similarity and Quality Measures. IEEE Information Reuse and Integration (IRI), July 2008: 82-85.

Vasilache, S. and Najarian, K. Automated Bone Segmentation from Pelvic CT Images. IEEE Bioinformatics and Biomedicine (BIBM), International Workshop on Biomedical and Heart Informatics (BHI), Nov. 3-5, 2008, Philadelphia: 41-47.

Smith, R. and Najarian, K. Automated Segmentation of Pelvic Bone Structure in X-Ray Radiographs Using Active Shape Models and Directed Hough Transform. IEEE Bioinformatics and Biomedicine (BIBM), International Workshop on Biomedical and Heart Informatics (BHI), Nov. 3-5, 2008, Philadelphia: 56-63.

Wang, J. and Liu, J. Video Authentication Against Correlation Analysis Attack in Wireless Network. 10th IEEE International Symposium on Multimedia (ISM 2008), Dec. 15-17, 2008, Berkeley, Calif.

Wang, J. and Choi, H. Defending against Middleman and Collision Attack in Wireless Networks. IEEE International Conference on Communications (ICC'09).

Gajic, Z., Lim, M., Skataric, D., Su, W. and Kecman V.2008. Optimal Control of Weakly Coupled Systems and Applications. CRC Press (Francis and Taylor).