Florent Krzakala is a professor at Sorbonne Université and a Researcher at Ecole Normale Superieure in Paris. His research interests include Statistical Physics, Machine Learning, Statistics, Signal Processing, Computer Science and Computational Optics. He leads the SPHINX “Statistical PHysics of INformation eXtraction” team in Ecole Normale in Paris, and is the holder of the CFM-ENS Datascience chair and of a PRAIRIE Institute chair. He is also the funder and scientific advisor of the startup Lighton.

- Professor UPMC and Researcher at Ecole Normale Superieure, Paris, Since 2013
- Member of the Institut Universitaire de France, Since 2015
- Holder of a Prairie Institute AI Chair, Since 2019
- Member and Fellow of the ELLIS society, Since 2019
- Holder of the chair CFM-ENS on datascience, Since 2016
- Visiting Professor @ Duke University, Maths Dept., 2018
- Visiting Scientist @ Simons Institute in Berkeley, 2016
- Visiting Scientist @ Los Alamos National Labs, 2008
- Maitre de Conference (Associate Professor) in ESPCI Paristech, 2004 - 2013

- Statistical Physics
- Machine learning
- Statistics
- Computer Science
- Random Optimization
- Signal Processing
- Information theory
- Inference on graphs
- Computational optics

Postdoc, 2004

Roma, La Sapienza

PhD in Statistical Physics, 2002

Orsay, Paris XI

MSc in Physics, 1999

Orsay, Paris XI

Current or recent classes

Lecture given in the international master Physics of Complex Systems on computational science

An introductory pratical course by Florent Krzakala and Antoine Baker, Ecole Doctorale EDPIF 2019

Cours Master 1, Université Paris Sorbonne 2019-2010

A set of Lectures given at Duke in 2018 by Lenka Zdeborova and Florent Krzakala

… and where to find them

Quickly discover relevant content by filtering publications.

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation.
*IEEE Transactions on Information Theory*.

(2020).
Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units.
*ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)*.

(2020).
(2020).
On the universality of noiseless linear estimation with respect to the measurement matrix.
*Journal of Physics A: Mathematical and Theoretical*.

(2020).
Detection limits in the spiked Wigner model.
Annals of Statistics.

(2020).