My research is at the intersection of deep learning, approximate inference and the physical sciences. Together with my collaborators and students, we have been developing a new generation of simulation-based inference algorithms based on deep learning, with several applications in particle physics, astrophysics, astronomy or gravitational wave science. Our long-term research objective is to unlock discoveries of a new kind by making AI a cornerstone of the modern scientific method.

PhD students


  • Antoine Wehenkel (2018-Present)
  • Norman Marlier (2018-Present, co-advised with Olivier Bruls)
  • Maxime Quesnel (2019-Present, co-advised with Oliver Absil)
  • Malavika Vasist (2019-Present, co-advised with Oliver Absil)
  • Arnaud Delaunoy (2020-Present)
  • François Rozet (2021-Present)
  • Omer Rochman (2021-Present)

Past students:

Open positions

To be announced.