Clickable word cloud describing CSE research areas. The relative relative word sizes represent the number of faculty working in each area. Photo credit: Christian Miller
The Department of Computer Science and Engineering conducts theoretical and applied research in AI, Theory and Algorithms, Software and Hardware Systems, and interdisciplinary areas related to CS+X such as Bioinformatics.
Focuses on the interplay between multiple elements of cyber technologies (such as sensing, computing, communications and control), and physical systems or processes (including infrastructures such as transportation and power) as well as human factors.
Focuses on efficient experimental and theoretical solutions to problems on state-of-the-art computational systems consisting of large numbers of computational elements, including clouds, clusters, grids, networks-of-workstations, massively parallel supercomputers, and GPU-based systems.
Focuses on developing highly efficient algorithms and techniques for a wide range of problems (such as automatic analysis of biomedical images, computer assisted diagnosis, treatment planning, protein-protein interaction network analysis, protein structure prediction, computational analysis and interpretation of Genomes, evolutionary studies of Genomic ORFans, and spatial positioning patterns of the cell nucleus) arising in smart hospital, smart healthcare, precision medicine, genomics, proteomics, and microarray analysis.
Mobile systems research focuses on the design and implementation of next-generation systems for mobile devices. Research topics include mobile data management, wireless networks, sensing systems, static analysis and instrumentation for mobile apps, mobile image and video analytics, and secure and low-power hardware for mobile devices.
Programming Language research focuses on type systems, program logics, language-based and differential privacy and security; language, compiler, and run-time design for reliable systems; static and dynamic analyses for real-time Android; run-time visualization and verification; adaptive memory management; language concepts for database programming; logic- and constraint-based systems.
Wenyao Xu created AutoDietary—software that tracks the unique sounds produced by food as people chew it. AutoDietary, placed near the throat by a necklace delivery system developed at China's Northeastern University, helps users measure their caloric intake.
Karthik Dantu owns the vision component of the RoboBee Initiative, led by the National Science Foundation and Harvard University. The "eyes" that Dr. Dantu is integrating are laser-powered sensors that enable the mechanical bees to orient themselves in space.
An article on PhysOrg reports UB has received a $584,469 grant from the National Science Foundation to create a tool designed to work with the existing computing infrastructure to boost data transfer speeds by more than 10 times, and quotes Tevfik Kosar, associate professor of computer science.
Ken Regan develops algorithms that detect cheating in chess games. His software compares a player's moves to a database of the player's typical gameplay, then makes an assessment of the statistical likelihood of cheating. Dr. Regan frequently consults at international chess matches.
Fei Xu and Bhargava Urala Kota, both PhD students in the Department of Computer Science and Engineering and part of UB’s Center for Unified Biometrics and Sensors (CUBS), received Best Paper Awards at the 15 International Conference on Document Analysis and Recognition (ICDAR).
Seventeen faculty and staff from the School of Engineering and Applied Sciences are among those who were honored for notable achievement, service and teaching at UB's 16th annual Celebration of Faculty and Staff Academic Excellence.
Three faculty and four staff members from the School of Engineering and Applied Sciences were among the 25 UB colleagues who have been named recipients of the 2019 SUNY Chancellor’s Award for Excellence, the most recipients from UB in recent history.
CSE Assistant Professor Nils Napp’s project, entitled “Abstraction Barriers for Embodied Algorithms,” addresses the problem of modeling physical interactions of robots in real-world environments. For example, a robot action can inadvertently change the state of the world, sometimes directly causing accidents or causing problems in future robot-world interactions. This project addresses this problem in the context of robot construction by developing representations of the world state that robots can reason about and use for planning. These allow programmers to treat robots and embodied algorithms and to make robots that reliably operate when modifying the environment and building structures.