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Jeff Bilmes

Jeff Bilmes
Associate Professor
Signal and Image Processing
418 EE/CSE
Box 352500
University of Washington
Seattle, WA 98195

Please visit my updated homepage as this page is not kept up to date.

Phone: (206) 543-2150
E-mail: bilmes __AT__ ee (dot) washington (dot) edu

University of California Berkeley, 1999 Ph.D.
Massachusetts Institute of Technology, 1993 M.S.
University of California Berkeley, 1989 B.S.

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Jeff A. Bilmes joined the University of Washington Department of Electrical Engineering faculty in the fall of 1999. He received a B.S. degree in Electrical Engineering and Computer Science from U.C. Berkeley in 1989, a S.M. degree from MIT in 1993, and a Ph.D. in Computer Science from U.C. Berkeley in 1999. He was also a member of the International Computer Science Institute in Berkeley, CA. He is the author of over 100 journal and conference papers on topics ranging from speech, language, statistical machine learning, human-computer interfaces, bio-informatics, pattern recognition, parallel programming, and high-performance software coding techniques.

Prof. Bilmes is also an adjunct associate professor in the University of Washington Department of Linguistics and in Computer Science and Engineering

His primary interests lie in statistical modeling (particularly graphical modeling approaches), combinatorial optimization, and signal processing for pattern classification, speech recognition, language processing, audio processing, and biological signal processing (bio-informatics). He also has strong interests in speech-based human-computer interfaces (and in fact is the principle investigator in the well-known vocal joystick system for speech based continuous control), the statistical properties of natural objects and natural scenes, information theory and its relation to natural computation by humans and pattern recognition by machines, and computational music processing (such as human timing subtleties). He is also quite interested in high performance computing systems, submodularity in machine learning, computer architecture, and software techniques to reduce power consumption.

While this front page is not kept up to date, more information, including the latest publications, can be found at my web page.

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