Yee Whye Teh
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]
Early life and education
Teh was born in Singapore in 1978. He received his secondary education at Dunman High School, graduating in 1994.
Teh then received his tertiary education 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]
Research and career
Teh was a postdoctoralfellow 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]
He has been a research scientist at Google DeepMind.[11]
Awards and honours
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.[12] 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]