Amos James Storkey (born 1971) is Professor of Machine Learning and Artificial Intelligence at the School of Informatics, University of Edinburgh.
[1][2][3][4] Subsequently, he has worked on approximate Bayesian methods, machine learning in astronomy,[5] graphical models, inference and sampling, and neural networks.
Storkey joined the School of Informatics at the University of Edinburgh in 1999, was Microsoft Research Fellow from 2003 to 2004, appointed as reader in 2012, and to a personal chair in 2018.
[6] In December 2014, Clark and Storkey together published an innovative paper "Teaching Deep Convolutional Neural Networks to Play Go".
Their paper showed that a Convolutional Neural Network trained by supervised learning from a database of human professional games could outperform GNU Go and win some games against Monte Carlo tree search Fuego 1.1 in a fraction of the time it took Fuego to play.