Our research group focuses on the development and application of artificial intelligence for the physical sciences. Our research work spans the following topics:

  • deep generative models (incl. normalizing flows, diffusion models, etc.)
  • architectures for scientific applications (incl. graph neural networks, neural operators, implicit neural representations, etc.)
  • simulation-based inference
  • applications in particle physics, astronomy, biophysics, oceanography, and weather science.

PhD students


  • 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)
  • Gérome Andry (2023-Present)
  • Victor Mangeleer (2023-Present)
  • Sacha Lewin (2023-Present)
  • Adrien De Voeght (2023-Present)

Former students:

Open positions

To be announced.