Research
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 make AI a cornerstone of the modern scientific method.
PhD students
Team:
- 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)
Former students:
- Joeri Hermans (2017-2022)
- Antoine Wehenkel (2018-2022)
Open positions
To be announced.