Yee Whye Teh

Yee-Whye Teh
Yee-Whye Teh
Alma mater	University of Waterloo (BMath) ; University of Toronto (PhD)
Known for	Hierarchical Dirichlet process ; Deep belief networks
	Scientific career
Fields	Machine learning; Artificial intelligence; Statistics; Computer science
Institutions	University of Oxford ; DeepMind ; University College London; University of California, Berkeley; National University of Singapore
Thesis	Bethe free energy and contrastive divergence approximations for undirected graphical models (2003)
Doctoral advisor	Geoffrey Hinton
Website	www.stats.ox.ac.uk/~teh/

Yee-Whye Teh is a professor of statistical machine learning in the Department of Statistics, University of Oxford. Prior to 2012 he was a reader at the Gatsby Charitable Foundation computational neuroscience unit at University College London. His work is primarily in machine learning, artificial intelligence, statistics and computer science.

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