Executive Officer: Professor Mikael Vejdemo-Johansson

The Graduate Center

365 Fifth Avenue

New York, NY 10016

Email: Compsci@gc.cuny.edu

https://www.gc.cuny.edu/computerscience

FACULTY

Sos Agaian, Asohan Amarasingham, Sergei Artemov, Amotz Bar-Noy, Raquel Benbunan-Fich, Peter Brass, Theodore Brown, Candido Cabo, Hui Chen, Soon Ae Chun, Louis D'Alotto, Saptarshi Debroy, Sven Dietrich, Susan Epstein, Nelly Fazio, Itai Feigenbaum, Elena Filatova, Linda Friedman, Rosario Gennaro, Izidor Gertner, Irina Gladkova, Mayank Goswami, Michael Grossberg, Jonathan Gryak, Feng Gu, Natacha Gueorguieva, Leonid Gurvits, Olympia Hadjiliadis, Yumei Huo, Susan Imberman, Shweta Jain, Ping Ji, Matthew Johnson, Tushar Jois, Delaram Kahrobaei, Akira Kawaguchi, Bilal Khan, Raffi Khatchadourian, Matluba Khodjaeva, Pegah Khosravi, Devorah Kletenik, TatYung Kong, Konstantinos Krampis, Yedidyah Langsam, Myung Jong Lee, Rivka Levitan, Sarah Levitan, Jun Li, Xiangdong Li, Michael Mandel, Lev Manovich, Tim Mitchell, Saad Mneimneh, Brian Murphy, Muath Obaidat, Alexey Ovchinnikov, Oyewole Oyekoya, Victor Pan, Rohit Parikh, Zheng Peng, Louis Petingi, Md Mahbubur Rahman, Anita Raja, Kaliappa Ravindran, Alla Rozovskaya, Paneer Santhalingam, Ashwin Satyanarayana, Subash Shankar, William Skeith, III, Dina Sokol, Katherine St. John, Ioannis Stamos, Bon Sy, Hao Tang, Abdullah Tansel, Ying-Li Tian, Felisa Vázquez-Abad, Mikael Vejdemo-Johansson, Huy Vo, Jie Wei, George Wolberg, Lei Xie, Noson Yanofsky, Sarah Zelikovitz, Danyang (Dan) Zhang, Jianting Zhang, Shuqun Zhang, Xiaowen Zhang, Zhanyang Zhang, Liang Zhao, Mingxian Zhong, Neng-Fa Zhou, Zhigang Zhu

THE PROGRAM

The Ph.D. Program in Computer Science is designed to prepare selected students for leadership in industrial careers and research as well as in teaching and academic research. The ubiquitous role of the computer in our society requires that the Ph.D. candidate master the discipline of computer science in its broadest sense as well as display knowledge of a specialized area and perform independent research.

Areas of Study

The program is particularly strong in the following specializations. (Please note that the division into areas of study is somewhat artificial; some courses are relevant to more than one area or, depending on the instructor’s focus, could be placed in another area.)

Programming Languages and Software Methodologies

Programming language development has been an active area of research in computer science almost from the origin of computer science itself. Nowadays, programming languages are defined formally. Stylistically, a programming language can be classified either as an imperative language or as a declarative language. Programs written by a user in a particular programming language should make use of computer software development methodologies. These methodologies not only foster good or correct practice in writing a program, but include techniques that cover the range of phased activities that a software product goes through from its conception through implementation to its maintenance. “Software Engineering” techniques are included in this category. Current faculty interests include formal methods of program description, verifying program correctness, declarative language construction, and mathematical linguistics.

Theoretical Computer Science and Its Applications

Predating the field of computer science, theoretical computer science is a mathematically rigorous study of computing. It includes a theory of computing machines, solvability, formal language theory, and concepts of timing. The area is so basic that it is often called “foundations.” Topics include formal languages, automata theory, computability and unsolvability, and logic of programs. Current faculty interests include computational geometry, security, recursion theory, applied logic, and computational complexity.

Artificial Intelligence, Cognitive Science, and Adaptive Systems

Artificial intelligence (AI) and cognitive science are concerned with developing algorithmic methodologies that can mimic various aspects of human performance and their implementation as computer programs. These methodologies include symbolic knowledge representation, concepts and methods of inference, modeling human thought, and sensory-motor performance. Cognitive science includes developing methodologies that model neural systems and adaptive dynamical systems. Current faculty interests include computational linguistics, data mining, natural language processing, learning and understanding systems, human locomotion and balance control, neural networks, logic in artificial intelligence, including logic programming, knowledge and belief, and image recognition systems.

Scientific Computing and Modeling of Systems

The original impetus for the creation of a computing machine was the need to do large-scale numerical computations. The field of numerical computation techniques continues to grow, with numerical calculations still playing an important role in scientific research. New approaches and techniques evolve that are quite general and powerful. Simulation of systems likewise plays an important role in scientific inquiry and more broadly in the design of all systems (including computer systems). Analytic modeling is another tool useful for analyzing the behavior of designed but not yet implemented systems. Current faculty interests include simulation of continuous and discrete systems, statistical modeling of systems, numerical algebra, numerical analysis, and biomedical computing.

Algorithms and Their Analysis

Algorithm design is at the heart of computing. Algorithms are the detailed procedures that in a finite number of steps accomplish a computing task. Thus this is a broadly defined category that impinges on all other areas. Current faculty interests include cryptography, combinatorial algorithm design, run time complexity, parallel and distributed algorithm design, and analysis of algorithms.

Computer Architecture, Networks, and Communications Systems

With the dynamic development of computer technology, hardware and computer architecture are important areas of research and development. The courses offered in this area include advanced computer architecture and computer/network communications. Current faculty research includes computer networks, parallel computation, neural nets, petri nets, and telecommunications.

Media Processing, Computer Vision, and Graphics

The design, distribution, display, recognition, storage schemes, large data sets, and multiple media in a document are important applied research areas in computer science. Medical information processing is a closely aligned research area. It teams physicians and computer scientists and has the potential of producing significant health-related goals. CUNY has a number of faculty members interested in this area. Current interests include graphics, computer vision, document understanding, database technology and document storage and retrieval, medical information processing, digital topological techniques for image processing, real-time processing of biomedical signals, and multiresolution approaches for image understanding.

Courses in the Ph.D. Program in Computer Science are offered at the Graduate Center as well as at Baruch College, Brooklyn College, the City College, Queens College, and the College of Staten Island.

Name	Degree	Type	NYSED Code	HEGIS Code	CIP Code
Computer Science	MPHIL - Master of Philosophy	Major	85074 - CSCI-MPHIL	0701.00	11.0701
Computer Science	PHD - Doctor of Philosophy	Major	85073 - CSCI-PHD	0701.00	11.0701
Data Science	MS - Master of Science	Major	39173 - DATASCI-MS	0702.00	30.3001
Data Science	ADVCERPB - Advanced Certificate Post Baccalaureate	Major	41585 - DSCP-AC	0702.00	30.3001

Department: Computer Science