Emmanuel Abbé

Mission Chair of Mathematical Data Science (SB/IC)The research in the chair of Mathematical Data Science (MDS) focuses on the mathematical principles that underpin the analysis and design of information and data science technologies. As branches of mathematics, this involves probability, statistics, and discrete mathematics, and as specific fields, machine learning and information theory. Please consult http://deepfoundations.ai/ for postdoc applications. Emmanuel Abbe received his Ph.D. degree from the EECS Department at the Massachusetts Institute of Technology (MIT) in 2008, and his M.S. degree from the Department of Mathematics at the Ecole Polytechnique Fédérale de Lausanne in 2003. He was at Princeton University as an assistant professor from 2012-2016 and an associate professor from 2016, jointly in the Program for Applied and Computational Mathematics and the Department of Electrical Engineering, as well an associate faculty in the Department of Mathematics at Princeton University since 2016. He joined EPFL in 2018 as a Full Professor, jointly in the Mathematics Institute and the School of Computer and Communication Sciences, where he holds the Chair of Mathematical Data Science. He is the recipient of the Foundation Latsis International Prize, the Bell Labs Prize, the NSF CAREER Award, the Google Faculty Research Award, the Walter Curtis Johnson Prize, the von Neumann Fellowship from the Institute for Advanced Study, the IEEE Information Theory Society Paper Award, and a co-recipient of the Simons-NSF Mathematics of Deep Learning Collaborative Research Award. Prof. E. Abbe is also a Global Expert at the Geneva Science and Diplomacy Anticipator (GESDA), a member of the Steering Committee of the Center for Intelligent Systems (CIS), EPFL, and director interim of the College des Sciences, EPFL. Enseignement et PhD Doctorant·es actuel·les Denys Pushkin, Ortal Yona Senouf, Vladyslav Shashkov A dirigé les thèses EPFL de Elisabetta Cornacchia, Aryo Lotfi Cours Reasoning in artificial intelligence MATH-700