Gilles Louppe is an Associate Professor in artificial intelligence and deep learning at the University of Liège (Belgium). Previously, he held positions as a Research Fellow at CERN and as Postdoctoral Associate at New York University with the Physics Department and the Center for Data Science.

His research is at the intersection of machine learning, artificial intelligence and physical sciences. Together with collaborators, he initiated and developed a new generation of simulation-based inference algorithms based on deep learning, with several applications to inference problems from particle physics, astrophysics, astronomy and gravitational wave astronomy. Louppe’s long-term research objective is to unlock discoveries of a new kind by making AI a cornerstone of the modern scientific method. His present research interests include:

  • simulation-based inference
  • probabilistic programming
  • deep generative models
  • bayesian deep learning
  • physics-informed deep learning
  • developments towards the automation of science


  • Joeri Hermans (2017-Present)
  • 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)