Dr. Peter Dayan is a world-renowned computational neuroscientist and director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, where he leads groundbreaking research at the intersection of neuroscience and artificial intelligence. He completed his mathematics studies at Cambridge University and earned his doctorate from the University of Edinburgh, followed by postdoctoral research with Terry Sejnowski at the Salk Institute and Geoffrey Hinton at the University of Toronto. In 1995, he joined MIT as an assistant professor before moving to London in 1998 to co-found the Gatsby Computational Neuroscience Unit, which he led as Director from 2002 to 2017. His distinguished career trajectory reflects his growing influence in bridging theoretical neuroscience with computational approaches, culminating in his 2018 appointment as Director of the Max Planck Institute for Biological Cybernetics. He also serves as Deputy Director of the Max Planck/UCL Center for Computational Psychiatry and Ageing Research and holds a Humboldt Professorship at the University of Tübingen.
Dr. Dayan pioneered the field of reinforcement learning, making seminal contributions to our understanding of how dopamine signals reward prediction error in the brain, and was instrumental in developing the influential Q-learning algorithm that underpins modern AI systems. His mathematical and computational models of neural processing have fundamentally transformed how scientists understand decision-making processes, representation, learning, and the role of neuromodulators in the brain. His co-authored textbook Theoretical Neuroscience has become a cornerstone reference in the field, shaping the education of countless researchers worldwide. Dr. Dayan's innovative applications of Bayesian methods from artificial intelligence to neural function have provided crucial insights into how neurotransmitter levels relate to prediction errors and uncertainty computations. His contributions to unsupervised learning, including the wake-sleep algorithm and Helmholtz machine, have had profound implications for both neuroscience and artificial intelligence.
His exceptional contributions have been recognized with prestigious awards including the Rumelhart Prize in 2012, The Brain Prize in 2017, and election as a Fellow of the Royal Society in 2018. Dr. Dayan's current research focuses on the intersection of computational approaches with psychiatric disorders, investigating how malfunctions in decision-making processes contribute to mental illnesses through the emerging field of computational psychiatry. He actively collaborates with diverse theoretical and experimental groups across the globe, including his participation in the International Brain Lab project, which aims to understand the neural basis of complex behavior. As a leader in applying theoretical frameworks to biological systems, his work continues to bridge the gap between artificial intelligence and neuroscience while addressing fundamental questions about brain function. His ongoing research is shaping how researchers approach the understanding and treatment of neuropsychiatric disorders through quantitative models that integrate neurobiological, psychological, and computational perspectives.
