The Les Houches school of physics has long and well known history of forming generations of young researchers on the frontiers of their fields. Our school is aimed primarily at the growing audience of theoretical physicists interested in machine learning and high-dimensional data analysis, as well as to colleagues from other fields interested in this interface. We will cover basics and frontiers of high-dimensional statistics, machine learning, theory of computing and learning, relevant mathematics and probability theory. We will focus in particular on methods of statistical physics and their results in the context of current questions and theories related to the before-mentioned fields. The school will also cover examples of applications of machine learning methods in physics research, as well as other emerging applications of wide interest. Open questions and directions will be presented as well.

Download the poster of the conference
Applications must reach the School by March 15, 2020. Fees, covering all local cost (logding+meals), will be circa 2000 euros.
The application form can be found on the school website.


  • Boaz Barak, Harvard, USA
  • Giulio Biroli, ENS Paris, France
  • Michael Jordan, UC Berkeley, USA
  • Marc Mézard ENS Paris
  • Yann LeCun (Facebook)
  • Remi Monasson, ENS Paris, France
  • Andrea Montanari, Stanford, USA
  • Maria Schuld, Univ. KwaWulu Natal & Xanada
  • Haim Sompolinsky, Harvard and Hebrew University of Jerusalem
  • Nathan Srebro, Chicago, USA
  • Miles Stoudenmire,Flatiron Institute, USA
  • Pierre Vandergheynst, EPFL Swiss

  Invited Speakers

  • Christian Borgs (UC Berkeley)
  • Jennifer Chayes (UC Berkeley)
  • Shirley Ho (Flatiron NYC)
  • Levent Sagun (Facebook AI)
  • More to be confirmed...

  Organizing Committee

  • Gerard Ben Arous(NYU, New York)
  • Surya Ganguli(Stanford)
  • Florent Krzakala (ENS, Paris)
  • Lenka Zdeborova (CEA & CNRS, Saclay)