Machine Learning

Sham Kakade joins UW Computer Science & Engineering and Statistics

Sham Kakade, a world-class expert in statistical machine learning, will join the University of Washington this fall as the holder of a Washington Research Foundation Data Science Chair appointed jointly in Computer Science & Engineering and Statistics, expanding UW’s excellence in data science and strengthening the connection between these two highly ranked programs.

Sham is currently Principal Research Scientist at Microsoft Research, New England. His research has ranged from economics to neuroscience to applied and theoretical machine learning and their intersection. He has made significant contributions to semi-supervised learning, online learning, reinforcement learning, and learning of latent-variable and hidden Markov models.

Prior to Microsoft Research, Sham was Associate Professor in the Wharton Statistics Department at University of Pennsylvania and Assistant Professor at Toyota Technological Institute, Chicago. He received his Ph.D. at the University College London Gatsby Computational Neuroscience Unit and his B.S. in Physics at Caltech.

Sham joins UW’s outstanding machine learning faculty including Carlos Guestrin, Pedro Domingos, Emily Fox, Daniela Witten, Marina Meila, Jeff Bilmes, Mathias Drton, Maryam Fazel, Noah Simon, and Thomas Richardson.


UW is one of the world's top centers of research in machine learning. We are active in most major areas of ML and in a variety of applications like natural language processing, vision, computational biology, the Web, and social networks. Check out the links on the left to find out who's who and what's happening in ML at UW.

And be sure to see our CSE-wide efforts in Big Data

 

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