Scholar
Quentin Bertrand
Google Scholar ID: Uxr3P78AAAAJ
Inria
Citations & Impact
Citations
482
H-index
11
i10-index
11
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Awarded joint ANR-NSERC 2025 funding to further work on the creativity of generative modeling; paper on generalization of flow matching deep generative models accepted at NeurIPS 2025 as an oral (top 0.3%); released a friendly blog post on normalizing flows and conditional flow matching techniques; recent works on self-consuming generative models and their biases gained media coverage from the N.Y. Times, Globe and Mail, etc.; launched a Python package for large scale optimization of sparse problems (4k downloads/month).
Research Experience
- Was a post-doctoral researcher at Mila from November 2021 to June 2024, working with Gauthier Gidel and Simon Lacoste-Julien; since July 2024, has been a tenured researcher (‘chargé de recherche’) at Inria Lyon, part of the Malice team located in Laboratoire Hubert Curien; became a Mila-affiliated member starting September 2025.
Education
- Completed his Ph.D. at Inria Paris-Saclay (Parietal Team) under the supervision of Joseph Salmon and Alexandre Gramfort, focusing on the optimization and statistical aspects of high dimensional brain signal reconstruction.
Background
- Research interests include generative models and multi-agent learning. More broadly, he studies how learning algorithms can leverage and interact with synthetic data from deep generative models.
Miscellany
- Contact: quentin [dot] bertrand AT inria [dot] fr
Co-authors