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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
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Pattern Recognition, Machine Learning, and Data Mining
Pattern
Recognition
Pattern recognition is the study of methods and algorithms for putting
data objects into categories. While classical pattern recognition techniques
are rooted in statistics and decision theory, the machine learning paradigm
is commonly used to design practical systems.
Machine
Learning
Machine learning is a method of programming computers where, instead of
designing the algorithm to explicitly perform a given task, the machine
is programmed to learn from an incomplete set of examples. There are several
different machine learning paradigms, such as the naive Bayes rule, artificial
neural networks, genetic algorithms, and decision tree learning.
Data Mining
Data mining is the extraction of ?nuggets? of information from structured databases. Algorithms for data
mining have a close relationship to methods of pattern recognition and machine learning. Information extraction
is the task of processing unstructured data, such as free-form documents, Web-pages and e-mail, so as to extract
named entities such as people, places, organizations, and their relationships.
Faculty
Laboratories and Research
Groups
- Center
of Excellence for Document Analysis and Recognition (CEDAR):
Director: Sargur N. Srihari
CEDAR performs research concerning scanned images of documents for the
purpose of intelligent interpretation. Current supporters include the
United States Postal Service, Lockheed Martin Federal Systems, and other
corporations.
- Center for Unified Biometrics and Sensors (CUBS):
Director: Venugopal Govindaraju
CUBS performs research on advancing the science of biometrics to provide key enabling technologies to build
engineered systems with focus on homeland security applications.
- Vision and Perceptual Machines Lab (VPML):
Director: Jason Corso
VPML performs research in computer and medical vision, computational biomedicine, machine perception, smart environments and interfaces.
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