Peter Dayan is the director of the Gatsby Computational Neuroscience Unit at the University College London. He is the a co-author of 'Theoretical Neuroscience', a leading textbook of computational and mathematical modeling of neural systems (see computational neuroscience). He is known for applying Bayesian methods from machine learning and Artificial Intelligence as theories of neural function, especially relating neurotransmitter levels to Bayesian uncertainties. He began his career studying Mathematics at Cambridge followed by a PhD in Artificial Intelligence at Edinburgh, which focused on reinforcement learning. He then went on to do a Postdoc at the Massachusetts Institute of Technology in Boston.

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