Yee-Whye Teh is a professor of statistical machine learning in the Department of Statistics, University of Oxford.[4][5] Prior to 2012 he was a reader at the Gatsby Charitable Foundation computational neuroscience unit at University College London.[6] His work is primarily in machine learning, artificial intelligence, statistics and computer science.[1][7]
Teh was educated at the University of Waterloo and the University of Toronto where he was awarded a PhD in 2003 for research supervised by Geoffrey Hinton.[3][8]
Teh was a postdoctoral fellow at the University of California, Berkeley and the National University of Singapore before he joined University College London as a lecturer.[2]
Teh was one of the original developers of deep belief networks[9] and of hierarchical Dirichlet processes.[10]
Teh was a keynote speaker at Uncertainty in Artificial Intelligence (UAI) 2019, and was invited to give the Breiman lecture at the Conference on Neural Information Processing Systems (NeurIPS) 2017.[11] He served as program co-chair of the International Conference on Machine Learning (ICML) in 2017, one of the premier conferences in machine learning.[4]
