Research Areas

Artificial Intelligence

Artificial Intelligence encompasses the study of algorithms and architectures that enable effective decision making in complex environments. Researchers in this area include faculty, undergraduate and graduate students working on projects in computer vision, robotics, virtual theatre, sensor networks, data mining, document recognition, and the theoretical foundations of decision-making (e.g. Markov chains and the properties of voting protocols).

Zachary Butler
Interim Department Chair

Cooperative robotics

Multiagent systems; computational social choice

Christopher Homan
Associate Professor

data science, machine learning, human computation

Ifeoma Nwogu
Assistant Professor
Alexander Ororbia
Assistant Professor

Document Recognition; Information Retrieval

Computer Graphics and Visualization

This area provides the technical foundations for studies in Computer Graphics. Areas for advanced study include Advanced Graphics Programming, Image Synthesis, Computer Animation, Virtual Reality, and Data Visualization.

virtual and augmented reality; motion capture; facial expression analysis; affective computing; tone reproduction

Interactive data visualization; stereo imaging of data

Warren Carithers
Associate Professor
Sean Strout
Principal Lecturer

applied visual perception; computer graphics; multimodal human sensing; eye-tracking

Visualization of scientific data

Computer Science Education

Explorations into the pedagogy of Computer Science focusing on new methods and paradigms for the teaching of the CS curriculum.

design and efficacy study of assignments promoting problem solving; automated feedback in CS theory

Zachary Butler
Interim Department Chair

design and efficacy study of assignments promoting problem solving; propagation of CS educational innovations

delivery of fundamental CS principles and assessment of student learning

interdisciplany collaborative coursework; computer graphics education

Xumin Liu
Associate Professor

service computing education; data science education;

data science education; cybersecurity education

Sean Strout
Principal Lecturer
Michael Mior
Assistant Professor

Interactive query visualization

Carlos R. Rivero
Associate Professor

automated feedback in programming assignments; automated repair of incorrect student programs

Data Science

Studies foundational data management and knowledge discovery challenges prevalent in design, analysis and organization of data. This area can be applied in a variety of domains including data management in resource constrained environments, enterprise and multimedia databases, active and secure databases and knowledge discovery algorithms.

Xumin Liu
Associate Professor

Large scale data management and data analytics; web services and service computing

Michael Mior
Assistant Professor

NoSQL databases; data integration

Efficient data management; data security and privacy

Carlos R. Rivero
Associate Professor

graph databases; knowledge graphs; graph mining

Social Network Analytics ; Data Visualization

Distributed Systems

This area studies systems formed from multiple cooperating computers. This includes the analysis, design, and implementation of distributed systems, distributed middleware, and computer networking protocols, including security.

Distributed Caching

Programmable networks; data center networks

Parallel and Distributed Computing; Pervasive and Mobile Systems

M. Mustafa Rafique
Assistant Professor

Resource management and distributed middleware; Data analytics and cognitive frameworks; Edge computing

Language and Tools

The Languages and Tools area studies language design and implementation together with architecture and use of software development tools.

Matthew Fluet
Associate Professor

Functional programming; Program analysis

Tools, frameworks, and languages supporting software modularity; CS education

Secure coding and languages

Security

The Security area spans topics from networking to cryptography to secure databases. By choosing different domains in which to study security students can gain a broad understanding of both theoretical and applied knowledge.

Warren Carithers
Associate Professor
Christopher Homan
Associate Professor

Internet of Things (IoT) security; network security

applied cryptography

data security and privacy; secure coding; cybersecurity education

Theory

The Theory area studies the fundamentals of computation. These fundamentals include complexity theory to determine the inherent limits of computation and communication and cryptography and the design and analysis of algorithms to obtain optimal solutions within those limits.

design and analysis of algorithms; counting and sampling problems

computational social choice; computational complexity; complexity of logics

Christopher Homan
Associate Professor

computational social choice; computational complexity 

combinatorial computing, computational Ramsey theory

Theory Seminar Series

The THEORY CANAL meeting (the Rochester Theory Seminar) is a joint project of the RIT and UR theory groups, and the focus is all areas of theoretical computer science. THEORY CANAL meets (when RIT and UR classes are in session) on the second and fourth Wednesdays of each month. Visit the THEORY CANAL website for more info on the series and the schedule of speakers.