Return to: Graduate Programs
ANUPAM JOSHI, Chair
CHARLES NICHOLAS, Graduate Program Director
M.S., Ph.D. (Degree Types )
BANERJEE, NILANJAN, Ph.D., University of Massachusetts; Embedded and distributed systems for mobile, pervasive and sustainability based computing: renewable energy driven mobile and sensor systems and health diagnostic systems; mobile system usability; mobile networking; experimental mobile testbed design.
FININ, TIMOTHY, Ph.D., University of Illinois, Urbana-Champaign; Artificial intelligence, knowledge representation and reasoning, knowledge and database systems, natural language processing, intelligent agents
JOSHI, ANUPAM, Ph.D., Purdue University; Networked/distributed and mobile computing, data/Web mining, multi-media databases, computational intelligence and multi-agent systems, scientific computing
LOMONACO, SAMUEL, Ph.D., Princeton University; Quantum computation, algebraic coding theory, cryptography, numerical and symbolic computation, analysis of algorithms, applications of topology to physics, knot theory and 3-manifolds, algebraic and differential topology, differential geometry
NICHOLAS, CHARLES, Ph.D., Ohio State University; Electronic document processing, software engineering, intelligent information systems
OATES, TIM, Ph.D., University of Massachusetts; Artificial intelligence, machine learning, robotics, natural language processing
PENG, YUN, Ph.D., University of Maryland, College Park; Artificial intelligence, neural networks, medical applications, artificial life (Emeritus)
PERKINS, DMITRI, Ph.D., Michigan State University, Wireless and Mobile Communications, Networking, Computer Systems , Network Security
PINKSTON, JOHN T., Ph.D., Massachusetts Institute of Technology; Coding theory, information security, quantam computing (Emeritus)
RUTLEDGE, JANET, Ph.D., Georgia Institute of Technology, Modeling and compensating for the effects of sensorineural hearing loss and other communication disorders
SHERMAN, ALAN T., Ph.D., Massachusetts Institute of Technology; Cryptology, discrete algorithms, and voting system security
SIDHU, DEEPINDER, Ph.D., State University of New York, Stony Brook; Computer networks, distributed systems, distributed and heterogeneous databases, parallel and distributed algorithms, computer and communication security, distributed artificial intelligence, high-performance computing
YESHA, YAACOV, Ph.D., Weizmann Institute, Israel; Parallel computing, computational complexity, algorithms, source coding, speech and image compression
YESHA, YELENA, Ph.D., The Ohio State University; Distributed systems, database systems, digital libraries, e-commerce, performance modeling, design tools for optimizing availability in replicated database systems, efficient and highly fault-tolerant mutual-exclusion algorithms, analytical performance models for distributed and parallel systems
YOUNIS, MOHAMED, Ph.D., New Jersey Institute of Technology; Distributed real-time systems; fault tolerant computing; wireless networks; embedded computer systems; compiler-based analysis; operating systems.
CHANG, RICHARD, Ph.D., Cornell University; Computational complexity theory, structural complexity, analysis of algorithms
KALPAKIS, KOSTAS, Ph.D., University of Maryland, Baltimore County; Digital libraries, e-commerce, databases, multi-media, parallel and distributed computing, combinatorial optimization
OLANO, MARC, Ph.D. University of North Carolina; Interactive procedural shading
PHATAK, DHANANJAY, Ph.D., University of Massachusetts, Amherst; Mobile and high-performance computer networks; computer arithmetic algorithms and their VLSI implementations; signal processing; neural networks and their applications and efficient implementations; digital and analog VLSI design and CAD
TING ZHU, Ph.D., University of Minnesota. Big Data, Embedded Systems, Cyber-Physical Systems, Mobile Systems, Distributed Systems, Operating Systems, Renewable and Sustainable Energies, Internet of Things, Wireless and Sensor Networks, Network Protocols, Social Networks, and Security.
BARGTEIL, ADAM, Ph.D., Computer Science, University of California, Berkeley. Computer graphics; animation; scientific computing; computational physics and computational geometry.
CHAPMAN, DAVID, Ph.D., University of Maryland, Baltimore County. Computer vision and machine learning applications to medical imagery, weather forecasting and robotics.
DEY, SANORITA, Ph.D.,University of Illinois at Urbana-Champaign, human-computer interaction, social computing, crowd computing, technologically mediated persuasive systems, and spatial learning.
FERRARO, FRANK, Ph.D. Johns Hopkins University. Natural language processing; machine learning; artificial intelligence.
MATUSZEK, CYNTHIA, Ph.D., University of Washington. Robotics, natural language processing, human-robot interaction, and artificial intelligence.
PIRSIAVASH, HAMED, Ph.D., University of California, Irvine, 2012. Computer Vision; Machine Learning and Multimedia.
RISLAM, IADUL, Ph.D., UC Santa Cruz, VLSI CAD tools and low-power digital and mixed-signal IC design.
LIU, CHENCHEN, Ph.D., University of Pittsburgh, high-performance computing for machine learning with novel computer architecture and system designs, brain-inspired computing, machine learning for computing security, novel non-volatile memory, and VLSI design.
VINJAMURI, RAMANA, Ph.D., University of Pittsburgh, brain-computer interfaces, neuroprosthetics and exoskeletons, machine learning, and signal processing.
HALEM, MILTON, Ph.D., New York University; high performance computing and communication, large-scale simulations, climate and environmental modeling
A list of the Computer Science faculty is also found at the department’s web site, https://www.csee.umbc.edu/people/
The department offers a graduate program leading to the M.S. and Ph.D. degrees in Computer Science. This program provides advanced instruction and training and research opportunities to prepare students for careers in industry, academia and government agencies. The program reflects state-of-the-art knowledge in major theoretical and applied aspects of computation. Fields of specialization in computer science (CS) include:
- Algorithms, theory and scientific computation (analysis of algorithms, algebraic coding theory, combinatorial optimization, computational complexity, cryptology, parallel computing, quantum computing, electronic voting)
- Computer networks and systems (computer and communication security, distributed systems, networks, parallel and distributed processing, wireless and mobile networks, optical networks, sensor networks)
- Databases, information and knowledge management (artificial intelligence, database systems, data mining, information retrieval, intelligent information systems, knowledge representation and reasoning, machine learning, natural language processing, neural networks, robotics, reasoning under uncertainty)
- Graphics, animation and visualization (animation, interactive 3D graphics, physically based modeling, procedural modeling, volumetric visualization and rendering)
A brochure is available that describes the department, its graduate programs, degree requirements and the research interests of the faculty. A copy can be obtained from the graduate program specialist or can be viewed from www.cs.umbc.edu.
Ongoing research in the department provides a source of project, thesis and dissertation topics for students. The previous list illustrates some of the current research areas. In addition, the department encourages interdisciplinary research and invites students to take advantage of resources in related departments, including education, geography, information systems, mathematics and statistics, physics, visual arts and other departments within the College of Engineering and Information Technology or at the University of Maryland, Baltimore (UMB) Medical School. In addition, opportunities exist for joint research projects with local research laboratories, companies and government agencies, including the Library of Congress, the NASA Goddard Space Flight Center, the National Institutes of Health, the National Institute of Standards and Technology, the National Security Agency and the Naval Research Laboratory.
Program Admission Requirements
When seeking admission to the graduate program, applicants must satisfy all entrance requirements of the Graduate School at UMBC. Applications are not processed until all documents and fees are received. All applicants must submit official transcripts, three letters of recommendation, statement of purpose, Graduate Record Examination (GRE General Test) scores and, for international students, scores for the TOEFL or IELTS. All original application documents must be sent directly to the Graduate School, not the graduate program. Application deadlines are specified by the Graduate School. The application review process will begin by February 15 for admission in the fall semester and by October 1 for admission in the following spring semester. Early application is recommended.
In addition to the requirements of the Graduate School, an applicant to the graduate program in computer science is expected to have a strong background in computer science and mathematics. This includes Calculus I and II, linear algebra and at least one more advanced course in mathematics. In addition, applicants are expected to have had the equivalents of the following computer science courses at UMBC:
CMSC 203: Discrete Structures
CMSC 313: Computer Organization and Assembly Language Programming
CMSC 331: Principles of Programming Languages
CMSC 341: Data Structures
CMSC 411: Computer Architecture
CMSC 421: Principles of Operating Systems
CMSC 441: Algorithm Design and Analysis
At least one course from the following list:
CMSC 435: Computer Graphics
CMSC 451: Automata Theory and Formal Languages
CMSC 455: Numerical Computation
CMSC 461: Database Management Systems
CMSC 471: Artificial Intelligence
CMSC 481: Computer Networks
Students may apply for admission to the Fall or Spring semesters. However, course selection and opportunities for financial aid are much better for Fall applicants. Students may apply for admission to either the M.S. or the Ph.D. program. However, admission to the Ph.D. program is highly selective, and only students with an exceptional background will be accepted. Students who plan to pursue the Ph.D. degree but who do not already have a master’s in computer science are advised to apply for admission to the M.S. program. New students will be assigned an academic advisor who can provide advice on choosing of courses, degree requirements and other important matters during the first year. By the end of the first year, students are expected to have identified a faculty member to serve as the research advisor for master’s or doctoral research. Consideration for continued financial assistance is dependent on identifying a research advisor. Admission to the M.S. and Ph.D. degree programs are separate.
Facilities and Special Resources
The department’s computing facilities include a variety of workstations, servers and high performance clusters. The UMBC Office of Information Technology has more than 400 workstations for general student use and several high-end machines. The university’s Imaging Research Center also provides high-end graphics support, including production quality input/output devices and production software
Financial aid is available on a competitive basis to a limited number of qualified graduate students in the form of graduate teaching assistantships (TAs), graduate research assistantships (RAs), work-study positions and hourly employment as graders. Graduate RAs are often available to students actively engaged in a master’s thesis or doctoral dissertation research and are awarded and renewed subject to availability of funds and satisfactory research progress. Students are encouraged to apply directly to nationally awarded fellowship programs.
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Return to: Graduate Programs