The computer science track of the Ph.D. in Engineering is designed for students who are interested in conducting advanced research in computer science.
The Master of Science in Computer Science emphasizes continuing self-development of individuals currently engaged in science, technology and engineering-related fields and prepares those who have completed undergraduate majors in these fields for entry into a career in computing technology.
The department also offers a Ph.D. in Engineering with a track in computer science. Applicants for this research-intensive doctoral program must hold an M.S. in Computer Science, and his or her intended area of research must be compatible with existing computer science research interests. The applicant must provide a statement of intended research (approximately one page in length) with his or her application. Ideally, the intended research will have been discussed previously with relevant faculty.
The department financially supports a limited number of graduate students, and such awards are made on a competitive basis. For details on graduate admission procedures, please refer to the information provided by the School of Engineering and the VCU Graduate School websites.
For Graduate Course Syllabi, please click here
For Graduate level certificates, please click here
The mission of the Ph.D. in Engineering degree program is to provide graduate students with learning opportunities for acquiring a broad foundation of engineering knowledge, an in-depth original research experience at the frontiers of engineering, and skills for lifelong learning and professional development. Graduates of this program will pursue careers in research and development or academia.
The program is designed to develop skills and educate CS students to be major contributors in the computing industry. The graduate program in computer science provides state-of-the-art education through the use of didactic courses to those students who wish to further their knowledge and careers within the computing industry.
Students accepted into this selective program accomplish both the B.S. and M.S. degrees within five years by taking additional graduate courses within the first four years of the program. Up to two of these courses will count as open electives in the B.S. program and as didactic course work in the M.S. program.
The Master of Science in Computer and Information Systems Security provides for the scholarly and professional needs of several groups who have either accepted or are keen to take on the challenge of protecting information resources of firms and society at large.
Students enrolled in computer science M.S. and Ph.D. programs can earn a Certificate in Cybersecurity. The Certificate will be signed by the Chair and Graduate Director.
The students must complete five graduate courses in the area of cybersecurity. The following courses count towards the certificate (at least 5 of these will be offered over a four-semester period):
- CMSC 512. Advanced Social Network Analysis and Security.
- CMSC 525. Introduction to Software Analysis, Testing and Verification.
- CMSC 612. Game Theory and Security.
- CMSC 615. Cryptocurrency and Blockchain Techniques.
- CMSC 618. Database and Application Security.
- CMSC 620. Applied Cryptography.
- CMSC 622. Network and Operating Systems Security.
- CMSC 623. Cloud Computing.
Certificate in Data Science
Students enrolled in computer science M.S. and Ph.D. programs can earn a Certificate in Data Science. The Certificate will be signed by the Chair and Graduate Director.
The students must complete five graduate courses in the area of data science. The following courses count towards the certificate (at least 5 of these will be offered over a four-semester period):
- CMSC 510. Regularization Methods for Machine Learning.
- CMSC 516. Advanced Natural Language Processing.
- CMSC 601. Convex Optimization.
- CMSC 603. High Performance Distributed Systems.
- CMSC 630. Image Analysis.
- CMSC 635. Knowledge Discovery and Data Mining.
- CMSC 636. Artificial Neural Networks and Deep Learning.
- CMSC 678. Statistical and Fuzzy Learning.
Dahlgren Academic Fellowship
Click here to learn more about the Dahlgren Academic Fellowship