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.
Algorithms for data mining have a close relationship to methods of pattern recognition and machine learning. Focuses on developing fundamental techniques, prototype systems and applications in databases and data science.
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.
Human-computer interaction (HCI) is a multidisciplinary field of study focusing on the design of computer technology, in particular, the interaction between humans (the users) and computers. HCI researchers observe the ways humans interact with computers and design technologies that allow humans to interact with computers in novel ways.
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.
Computing is ubiquitous in society today. Computing touches all aspects of our lives and sometimes in ways that are not beneficial (even though the intent of the developer is not to cause harm). What has become clear is that we cannot develop systems for society without meaningful and deep collaborations with disciplines that have thought about society for much longer than computing. The challenge is to incorporate knowledge from humanistic studies from day one in the design of computing systems.
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.
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.
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.
Shambhu Upadhyaya received a 2021-22 Excellence in Graduate Student Mentoring Award, presented by the Graduate School to recognize UB faculty for their support and development of graduate students through their mentoring activities.
Michael Langberg, Siwei Lyu and Shambhu Upadhyaya have been elected Fellows of IEEE, a professional organization dedicated to advancing technology and fostering technological innovation for the benefit of humanity.
Agarwal was recognized for his work on ‘detecting and mitigating a spectrum of attacks at the data level to protect the integrity of various biometrics and computer vision algorithms using machine learning algorithms’.