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Computer Science Faculty Research

Stamos

Hunter College Associate Professor Ioannis Stamos, left, and City College Professor George Wolberg with Hunter's 3D Leica HDS 2500 camera that scanned Shepard Hall (in background).

Diversity of Interest & Exploration

Research interests within the department span many areas, including computational biology and bioinformatics, computer vision and image processing, computational linguistics and natural language processing, computer and network security, machine learning and knowledge representation, program verification, and graph theory.

 

FacultyResearch Interests
Susan Epstein artificial intelligence, machine learning, spatial cognition, thinking
Raffi Khatchadourian programming languages, software engineering, and Machine Learning systems
Wole Oyekoya Virtual, Augmented and Mixed Reality, Scientific and Data Visualization.
Anita Raja Distributed Artificial Intelligence, Meta-level Reasoning, Machine Learning, Complex Networks
Katherine St. John Computational Biology, Trees, Random Structures & Algorithms
Ioannis Stamos Computer Vision, Robotics, Computer Graphics, Artificial Intelligence, 3D Visualization

Bioinformatics & Artifical Intelligence

Susan Epstein's research seeks pragmatic solutions to hard problems. She and her students are currently at work on constraint satisfaction, pattern discovery for bioinformatics, and natural language dialog for a real-world environment. These are challenging and exciting projects that involve thinking about how people do things and the role that visualization plays in our ability to reason. As a result, her work in artificial intelligence is primarily directed to knowledge representation (how to describe the world to a machine) and machine learning (how a machine can improve its performance based on its experience). Many undergraduate researchers have started their careers under Prof. Epstein's tutelage and have since entered doctoral programs in computer science.

Switching Algorithms & Computational Biology

Saad Mneimneh works on switching algorithms and networks and he is part of the Quantitative Biology program in Hunter conducting research in computational biology. He has also spent time developing new pedagogy to bring a level of mathematical thinking into courses such as computer programming, computer networks, and discrete structures, in order to develop critical and formal thinking skills.

Computational Biology & Software Engineering

Stewart Weiss is also involved in computational biology and has been studying protein structure prediction algorithms. This is a relatively new interest for him. Prior to this, he was involved in the creation and analysis of psychometric algorithms for diagnostic eye testing as well as algorithms for 3D reconstruction of corneal topography from 2D images. He spent many years in the field of software testing and formal methods in software engineering before turning his attention to these other areas.

Formal Methods

Subash Shankar is presently working in the area of formal methods for software and embedded systems. His current projects focus on static analysis and formal verification of reactive languages used to describe embedded systems. In support of these projects, he is also developing languages for high-level constraint-based reasoning over graphically structured data.

Computer Models Of Human Language & Human Language Acquisition

William Sakas is interested in computer models of human language and human language acquisition. One important research question that he is trying to answer is, what are the critical and fundamental components of a computational model of language and how accurately are they correlated with empirical psycholinguistic data? His research methods draw from computational linguistics, computational psycholinguistics, machine learning, probabilistic modeling, corpus analysis, psycholinguistics, linguistic theory and computational learning theory.

Computational Linguistics & Bioinformatics

Virginia Teller spent most of her research career in computational linguistics. In her role as department chair, she has turned her attention to computer science education, and has spent considerable effort in co-creating the Bioinformatics track in computer science and in trying to increase the numbers of women and minorities in the PhD pipeline. She, Stewart Weiss, and Mary Flanagan (formerly of the Department of Film and Media Studies) were co-PIs on an NSF-sponsored project with this as its objective.

Graph Theory & Networks

Christina Zamfirescu's most recent research focuses on two directions, both within graph theory and networks. One is involved with intersection digraphs, a concept she introduced with L.W. Beineke, and its connections to transformation digraphs and system complexity measures. The other one deals with the hamiltonicity of topological grid graphs.

Quantitative Reasoning

Cullen Schaffer has been developing various ideas about teaching quantitative reasoning using computers as a tool for thinking. He has developed a course called Computers and Money that explores mathematical modeling in a manner accessible to students with only a basic foundation in arithmetic. He has a background in data analysis and is also active in computer-based language learning.

Quantum Computing

Eric Schweitzer is the resident tinkerer and philosopher. He is a mathematician and logician, but spends much of his time in the hardware lab building this and that, and trying to get our students to do the same. He is sure that this polar dichotomy explains his current infatuation with quantum computing.

Computer Science, Intellectual Property Rights & The Law

Last but not least, is Daniel Cohen. Daniel Cohen has written books on combinatorics, formal languages, and automata theory, and has worked in discrete mathematics for most of his career. Late in his career, he studied law and passed his bar exams, and now studies the fuzzy areas between computer science, intellectual property rights, and the law. He relishes an audience and has guided many undergraduates in their post-graduate career paths.

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