Erik B. Sudderth, Statistical Computation & Perception

I am a Professor of Computer Science and Statistics, and Chancellor's Fellow, at the University of California, Irvine. My Learning, Inference, & Vision Group develops statistical methods for scalable machine learning, with applications in artificial intelligence, computer vision, and the natural and social sciences. My research affiliations at UC Irvine include:

For a tutorial introduction to probabilistic modeling and approximate inference, see the background chapter of my doctoral thesis, advised by Professors Alan Willsky and William Freeman at MIT EECS. My postdoctoral research at Berkeley EECS, advised by Professors Michael Jordan and Stuart Russell, focused on Bayesian nonparametric models (see my CVPR tutorial).

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Research Highlights

Editorial Highlights

Erik Sudderth
Erik B. Sudderth
P: (949) 824-8169

Office: Donald Bren Hall 4206
Mailing Address:
University of California, Irvine
School of Information & Computer Sciences
Irvine, CA 92697-3435
UC Irvine