Gabriel Peyre

PEYRÉ Gabriel

Applied mathematics

gabriel.peyre [at]

Short bio

CNRS research director and professor at Ecole Normale Supérieure. Director of the data sciences center of the ENS. Blaise Pascal Prize 2017 of Académie des sciences, Magenes prize 2019 from the UMI. ERC starting grant 2012, ERC consolidator grant 2017.

Topics of interest

Optimal transport, imaging sciences, machine learning

Project in Prairie

The goal of my research project is to scale Optimal Transport methods both computationally and statistically to handle high dimensional machine learning problems. As deputy scientific director of PRAIRIE, I help to coordinate the research and teaching effort of the project. I am also be involved through my chair in fundamental and collaborative researches, as well as in teaching and dissemination of research.


Optimal transport (OT) is a fundamental mathematical theory at the interface between optimization, partial differential equations and probability. It has recently emerged as an important tool to tackle a surprisingly large range of problems in data sciences, such as shape registration in medical imaging, structured prediction problems in supervised learning and training deep generative networks.


PhD student

Postdoctoral researcher
MA (Mathematics), MA (History of Science), PhD (History of Science), University of Wisconsin-Madison