With a background in artificial intelligence and biomathematics, Peggy Seriès did her PhD in computational neuroscience in Paris with Yves Frégnac and Jean Lorenceau and postdocs with Alexandre Pouget at University of Rochester, Peter Latham at the Gatsby Computational Neuroscience Unit in London and Eero Simoncelli at NYU. She was then working on models of the visual cortex, questions related to population coding, information transmission and Bayesian theories of the brain. She joined the School of Informatics at the University of Edinburgh in 2006 where she was recently promoted as a Full Professor in Computational Psychiatry.
Peggy’s current interests centre on computational models of cognition, with a particular emphasis on learning and decision making and their application for the understanding of mental illness. Her research projects aim at a better understanding of behavioural differences in schizophrenia, depression, anxiety and autism and their underlying neurobiological mechanisms. In 2020, she has edited the first accessible textbook in the emerging domain of Computational Psychiatry (“Computational Psychiatry: a Primer”, MIT Press).