ABSTRACT: TBC

BIO:

Marc Mezard is a Professor of Theoretical Physics. He studied physics at Ecole normale supérieure in Paris and obtained his PhD in 1984. Hired at CNRS in Paris, he was Research Director in Université Paris Sud starting in 2012. In 2022 he became Director of Ecole normale supérieure, and  then joined Bocconi University as a professor, in the newly created department of computational sciences.  His work focuses on statistical physics of disordered systems, with applications in various fields like information theory, computer science, machine learning, biophysics.

Mezard is interested in the emergent phenomena in complex systems with many interacting “atoms”, (that could be for instance agents on a market, information bits, or molecules are different or live in different environments.) The statistical physics of disordered systems that he contributes to develop finds applications in various branches of science – biology, economics and finance, information theory, computer science, statistics, signal processing. In recent years his research has focused on information processing in neural networks, machine learning and deep networks. He is particularly interested in the theoretical impact of data structure on learning strategies and generalization performance.