Publications

Books written by CS faculty

Book cover for data mining methods for knowledge discovery
Book cover for medical data mining and knowledge discovery
Book cover for data mining: a knowledge discovery approach
Book cover for the design of collaborative intrusion detection networks
Book cover for Learning and Soft Computing
Book cover for Machine Learning by Adaptive Local Hyperplane Algorithm
Book cover for Optimal Control
Book cover for Lecture Notes in Control and Information Sciences
Book cover for Kernel Based Algorithms for Mining Huge Data Sets
Book cover for Learning from Imbalanced Data Sets
Hyperbolic Partial Differential Equations Vol 1
Hyperbolic Partial Differential Equations Vol 3
Computational Medicine, Public Health and Biotechnology Part 1
Computational Medicine, Public Health and Biotechnology Part 2
Computational Medicine, Public Health and Biotechnology Par 3
Mathematical Models in Medicine

2017 faculty publications

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, http://wires.wiley.com/WileyCDA/WiresArticle/wisId-WIDM1232.html 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 28th 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.schscipages.com/Articles/artificial-intelligence/the_scientific_pages_of_artificial_intelligence-tspai-1-001.php?jid=artificial-intelligence; 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 specialised 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, https://goo.gl/Cg3FHy

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   https://dl.acm.org/citation.cfm?id=3078526 (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 3rd 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 https://goo.gl/Cg3FHy (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 http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2661345

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 http://cda.currentprotocols.com/WileyCDA/CPUnit/refId-ps0216.html

2016 faculty publications

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. http://www.fisem.org/www/union/revistas/2016/46/01_13-307-1-ED.pdf 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 https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw280 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. http://business.bnu.edu.cn/IIKI2016/iiki2016.pdf

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. http://euc2016.conferences-events.org/files/euc_cse_dcabes_2016.pdf

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. http://dl.acm.org/citation.cfm?id=2935649

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

2015 faculty publications

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 http://nar.oxfordjournals.org/content/43/18/e121IF 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 http://bib.oxfordjournals.org/content/16/5/780IF 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.

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 42nd 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. http://bionetics.org/2015/show/accepted-papers

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. http://bionetics.org/2015/show/accepted-papers.

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. http://bionetics.org/2015/show/accepted-papers.

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. http://bionetics.org/2015/show/accepted-papers.

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

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.)

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.)