Florent Krzakala

Florent Krzakala

Full Professor

École polytechnique fédérale de Lausanne

About me

Florent Krzakala is a full professor at École polytechnique fédérale de Lausanne in Switzerland. His research interests include Statistical Physics, Machine Learning, Statistics, Signal Processing, Computer Science and Computational Optics. He leads the IdePHIcs “Information, Learning and Physics" laboratory in the Physics and Electric Engineering departments in EPFL. He is also the founder and scientific advisor of the startup Lighton.

Interests
  • Statistical Physics
  • Machine learning
  • Probability and Statistics
  • Computer Science
  • Information theory
  • Inference on graphs
  • Random Constraint Optimization
  • Computational optics
Education
  • Postdoc, 2004

    Roma La Sapienza

  • PhD in Statistical Physics, 2002

    Orsay, Paris XI, France

  • MSc in Physics, 1999

    Orsay, France

Former members (and where to find them)

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Alia Abbara

EPFL, Lausanne

Postdoc

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Antoine Baker

ENS, Paris

Postdoc

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Jean Barbier

Trieste, ICTP

Professor

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Francesco Caltagirone

SONOS

Research Engineer

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Jonathan Dong

EPFL, Lausanne

Postdoc

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Angelique Dremeau

ENSTA

Assoc. Professor

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Laura Foini

CNRS, Ipht Saclay

Researcher

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Marylou Gabrie

Ecole Polytechnique, Paris

Professor

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Cedric Gerbelot

NYU, New York

Courant Instructor

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Sebastian Goldt

SISSA, Trieste

Professor

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Alejandro Lage

University La Havana, Cuba

Professor

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Julien Launay

Researcher at HuggingFace

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Bruno Loureiro

ENS and CNRS, Paris

Researcher

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Antoine Maillard

ETHZ, Zurich

Hermann-Weyl Instructor

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Andre Manoel

Microsoft

Research Engineer

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Ruben Ohana

Simons Center, New York

Postdoc

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Boshra Rajaei

Sadjad Univ.

Assoc. Professor

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Maria Refinetti

G-research, London

Researcher

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Alaa Saade

Google Deepmind

Research Engineer

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Luca Saglietti

Bocconi University, Milan

Professor

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Christophe Schulke

Phillips research

Researcher

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Gabriele Sicuro

Universita di Bologna

Professor

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YIfan Sun

Renmin university, China

Lecturer

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Eric Tramel

UNLEARN.AI

Team Lead

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Rodrgigo Veiga

EPFL

Postdoc

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Pan Zhang

Institute of Theoretical Physics, Beijing

Professor

Recent classes

Fundamentals of inference and learning EE-411
EPFL set of lectures on the theory of statistics, inference, and machine learning.
Fundamentals of inference and learning EE-411
Mecanique quantique et théorie des groupes
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Mecanique quantique et théorie des groupes
Numerical Physics and Machine Learning
Lecture Master 2, Ecole Normale Superieure 2020-2021, ICFP
Numerical Physics and Machine Learning
Statistical Physics For Optimization and Learning
A set of Lectures given at Duke in 2018 by Lenka Zdeborova and Florent Krzakala
Statistical Physics For Optimization and Learning
Statistical Physics For Optimization and Learning
A Set of Lectures given at EPFL in 2021 by Lenka Zdeborova and Florent Krzakala
Statistical Physics For Optimization and Learning

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