Honglak Lee’s primary research interests lie in machine learning, which spans over deep learning, unsupervised and semi-supervised learning, transfer learning, graphical models, and optimization. He also works on application problems in computer vision, audio recognition, robot perception, and text processing. He has served as a guest editor of IEEE Transactions on Pattern Analysis and Machine Intelligence Special Issue on Learning Deep Architectures, as well as area chairs and senior program committee of the International Conference on Machine Learning, Neural Information Processing Systems, International Joint Conferences on Artificial Intelligence, and the International Conference on Computer Vision. He was selected by IEEE Intelligent Systems as one of AI’s 10 to Watch in 2013.
Best paper award, International Conference on Machine Learning, 2009.
Best paper award, Conference on Email and Anti-Spam, 2005.
Google Faculty Research Award, 2011.
Associate Fellow Learning in Machines & Brains
University of MichiganComputer Science & Engineering Division
Ph.D., Computer Science Department Stanford University
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