Timothy Lillicrap, Google DeepMind and UCL, UK
Timothy P. Lillicrap is a Canadian neuroscientist and AI researcher, adjunct professor at University College London, and staff research scientist at Google DeepMind, where he has been involved in the AlphaGo and AlphaZero projects mastering the games of Go, Chess and Shogi. His research focuses on machine learning and statistics for optimal control and decision making, as well as using these mathematical frameworks to understand how the brain learns. He has developed algorithms and approaches for exploiting deep neural networks in the context of reinforcement learning, and new recurrent memory architectures for one-shot learning.[1] His numerous contributions to the field have earned him a number of honors, including the Governor General’s Academic Medal, an NSERC Fellowship, the Centre for Neuroscience Studies Award for Excellence, and numerous European Research Council grants. He has also won a number of Social Learning tournaments.
https://en.wikipedia.org/wiki/Timothy_Lillicrap
https://scholar.google.co.uk/citations?user=htPVdRMAAAAJ&hl=en
https://contrastiveconvergence.net/~timothylillicrap/index.php