Areas of Research Concentration

Research Areas

• Algorithms and Theory

• Augmentative Technology for the Handicapped

• Computer Networks and Distributed Systems

• Computer Science Education

• Computer Security and Information Assurance

• Computer Vision and Information Visualization

• Databases

• High-Performance and Grid Computing, Cyberinfrastructure, and Computational Science

• Knowledge Representation, Computational Linguistics, and Cognitive Science

• Medical Applications and Bioinformatics

• Multimedia Databases and Information Retrieval

• Pattern Recognition, Machine Learning, and Data Mining

• Programming Languages and Software Systems

• VLSI and Computer Architecture

Research Centers, Labs, and Groups Home Pages

• Center for Unified Biometrics and Sensors

• Center of Excellence for Document Analysis and Recognition

• Center of Excellence in Information Systems Assurance Research and Education

• Bioinformatics Research Group

• Database and Multimedia Research Group

• Distributed Systems Research Group

• Knowledge Media Lab

• Laboratory for Advanced Network Design, Evaluation, and Research

• Language Research Group

• Logical Foundations of Databases Research Group

• Multimedia Information Retrieval

• MultiStore Research Group

• Security, Dependability, and Test Design Automation (SPIDER)

• SNePS Research Group

Facilities

• About Facilities

• Labs

• Special-Purpose Computing

• Research Computing

• Faculty/Staff Computing

• Infrastructure

Departmental Technical Reports

• Technical Report Archive

• Technical Reports submission instructions

• CSE Library and Research Resources

Computer Vision and Information Visualization

Computer vision is an interdisciplinary field drawing on concepts from signal processing, artificial intelligence, neurophysiology, and perceptual psychology. The primary goal of computer vision research is to endow artificial systems with the capacity to see and understand visual imagery at a level rivaling or exceeding human vision. One part of research at UB focuses on computational theories for contour image analysis of things such as technical drawings, architectural plans, maps, and even cartoons to enable such images to be used in human and computer interaction. With psychophysical experiments, aspects of contour images of perceptual significance to humans are identified.

Active foveal vision explores the use of cameras whose resolution decreases from center to periphery of the field of view, similar to the human retina. This research focuses on the design of computer chips to implement a system that registers a central region of interest with high detail while displaying a larger zone at lower resolution, and on the algorithms that permit variable resolution image sequences to be understood.

Our fundamental research includes developing techniques for visualizing common data-structures such as graphs and multidimensional data sets, and visualizing molecular structures. Our applied research includes visualizing data from practical applications, such as bioinformatics, software engineering, pharmacokinetics, engineering and design, bioimaging, and digital art.

Faculty

• Peter Scott (Associate Professor)
• Jason Corso (Assistant Professor)

Knowledge Media Lab Projects

• Using Technology to Improve Learning and Decrease Cost
• Community Linked Interdisciplinary Research

	Did You Know

CSE faculty averages some $4.5 million annually in grants for research in areas that range from high-performance computing to data mining.

CSE faculty are major participants in the new $200 million Buffalo Center of Excellence in Bioinformatics.

CSE's MultiStore Research Group is funded by a $1 million NSF grant for the development of high-performance online data-storage systems.

A CSE-affiliated research center developed the systems that postal agencies around the world use for automatically sorting hand-addressed mail.

CSE faculty work with researchers in chemistry, the life sciences, the pharmaceutical sciences, media study, geography, and many other disciplines.

The CSE-affiliated Center for Computational Research is one of the leading academic supercomputing centers in the U.S.

The CSE faculty includes NSF CAREER award holders and ACM, IEEE, and AAAI fellows.

A geometric algorithm developed by CSE professor Jinhui Xu configures a set of radiation beams to destroy brain tumors in a form of computer-aided surgery.

CSE professor Aidong Zhang is developing intelligent content-analysis programs to automatically analyze images, replacing human coding of semantic content.

CSE professor Russ Miller is one of the authors of a program that can determine the structure of molecules as large as 2,000 atoms from X-ray diffraction patterns.

Pursuing work on document verification and identification, CSE researchers use machine-learning algorithms to study handwriting variability.