Full Professor at EPFL (École polytechnique fédérale de Lausanne)
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I am a professor and researcher specializing in statistical physics, machine learning, and applied mathematics. My work spans neural networks, optimization, statistics, spin glasses and information theory.
Pierre and Marie Curie University
Ph.D, Theoretical Physics
January 1, 1998 – January 1, 2002
Aix-Marseille University
Maitrise/Undergraduate studies, Physics
January 1, 1994 – January 1, 1998
EPFL
Full Professor
September 1, 2020 – Present
Lausanne, Vaud, Switzerland
Duke University
Visiting Professor
January 1, 2018 – May 1, 2018
Duke, North Carolina, United States
Krzakala, inc
Formation in Machine Learning
November 1, 2017 – September 1, 2020
Paris Area, France
Ecole normale supérieure
Deep learning lecturer
October 1, 2017 – September 1, 2020
Paris Area, France
LightOn
co-founder and scientific advisor
June 1, 2016 – Present
Paris Area, France
UC Berkeley
Visiting Scientist
January 1, 2016 – May 1, 2016
Simons Institute
Institut Universitaire de France
Membre Junior
September 1, 2015 – September 1, 2020
Ecole normale supérieure
Researcher
September 1, 2013 – September 1, 2020
Paris Area, France
UPMC - Sorbonne Universities
Full Professor
September 1, 2013 – September 1, 2020
Paris
Los Alamos National Laboratory
Visiting Researcher
January 1, 2008 – January 1, 2010
Los Alamos, New Mexico
ESPCI
Assistant professor
September 1, 2004 – September 1, 2013
University of Rome "La Sapienza"
Post-doctorat fellow
September 1, 2002 – September 1, 2004
Rome Area, Italy
Cultural Fit Analysis
The candidate's background is heavily academic and research-oriented, with a recent pivot towards Machine Learning and Deep Learning. While this demonstrates intellectual curiosity and adaptability, the direct alignment with a typical corporate 'Data Analyst' role, which often requires specific business domain understanding, SQL proficiency, and dashboarding tools, is not immediately evident. The breadth of skills is strong in theoretical and advanced ML/DL, but less so in standard data analysis tools and practices. The candidate's experience as a co-founder and professor suggests a preference for innovation and leadership, which could be a good fit for a data science team with a strong research component, but might require adjustment for a more routine data analyst position.
Soft Skills & Operational Fit
The candidate's extensive academic and research career suggests strong analytical thinking, problem-solving, and independent work capabilities. Roles as a professor and lecturer imply strong communication and presentation skills. Co-founding a company indicates initiative and a results-oriented mindset. However, direct operational experience in a corporate data analyst role is not explicitly detailed.