Jean-Pierre Nadal

Curriculum Vitae (French version here)

photo copyright J.-P. Nadal 2008


Born March 1st, 1957, Paris - Citizenship: French
Maried, two children (here and here).


Diplomas
1980 Engineer diploma from Ecole Polytechnique
1981 Diploma of Advanced Studies (DEA/Master) in Theoretical Physics (University Paris XI)
2/83 3rd cycle Thesis ("Thèse de 3ème Cycle"), University Paris XI (Advisor: Jean Vannimenus, GPS ENS).
2/2/87 Doctorate ("Doctorat d'Etat"), University Paris XI (Advisor: Jean Vannimenus, GPS ENS).


Positions
9/77 - 8/80 Student at Ecole Polytechnique
10/80 - 9/83 Research scholarship from Ecole Polytechnique
10/83 - Researcher at CNRS:
10/83 - 9/88 Researcher (CR2)
10/88 - 9/98 Researcher (CR1)
10/98 - 9/13 Senior researcher (DR2)
10/13 - Senior researcher (DR1)
10/12 - Director of studies at EHESS
Host laboratory:
10/83 - 12/87 Solid State Physics Group (GPS), Ecole Normale Supérieure (ENS).
9/84 - 8/85 Physics Department, University of California, Berkeley, USA
1988 - 2018 Laboratoire de Physique Statistique (LPS), Ecole Normale Supérieure.
2019 - Physics Laboratory of the Ecole Normale Supérieure (LPENS)
2006 - Part time at the ENS, and at the
Centre d'Analyse et de Mathématique Sociales (CAMS), EHESS

Award
1989 CNRS Bronze Medal


Teaching activity
1990 - 2004 : Advance Studies (DEA) in Cognitive Science (EHESS, Paris 6, Ecole Polytechnique, ENS)
2004 - : Master in Cognitive Science ("Cogmaster" EHESS, ENS, Paris 5, ENS de Cachan)
1999 - : Master (M2) "Maths Vision Apprentissage" (MVA), ENS de Cachan
details and other teaching activities, see here Consulting 1989 - 1996 Consulting activity mainly with LEP (Laboratoires d'Electronique Philips S.A.S.) Invited talks see here Research activities see here Publications see here Detailed CV (in French, and old: 2013) see here (pdf file)


Research trajectory

With a general maths and physics background, and a specialisation in theoretical physics, my earliest research works are in the domain of the statistical physics of disordered systems. I worked mainly on the statistical physics of "lattice animals" - percolation type models studied both in physics and in combinatorics.

In the mid 80's I turned to the modelling of neural networks, following the pioneering work of J. J. Hopfield on attractor neural networks. Since then my main contributions in the domains of neural networks and computational neuroscience have been in the modelling of short term memory in the human brain, the theory of supervised and unsupervised learning, and in the study of neural coding making use of both statistical physics and information theoretic tools. In the recent years I have been involved in collaborations with biologists. Some of my most recent works are motivated by problems at the boundary between linguistics and neuroscience (in particular in collaboration with psycholinguists). This lead me to study the neural coding of phonemes, and the neural mechanisms underlying decision making in multichoices tasks.

While working on problems motivated by the modelling of human cognitive processing, I have also addressed issues in the related fields of machine learning (theoretical and practical algorithmic aspects within the supervised learning framework), statistical inference, data analysis (in particular in bioinformatics) and signal processing (notably working on blind source separation and independent component analysis). The analysis of optimal neural coding also lead me to study of the statistical properties of natural images. Finally, during about ten years I have been acting as a consultant for a private research laboratory, working on applications of machine learning techniques.

My first work in the field of economic and social science dates back to the mid 90's, a collaboration on the topic of market organization with Gérard Weisbuch at the ENS and the economist Alan Kirman, EHESS. Since 2002, I work on collective phenomena in economic and social sciences in collaboration with physicists, mathematicians, economists and other social scientists.