Nicolas Jouvin
Researcher in Statistics & Machine Learning, Université Paris-Saclay/AgroParisTech/INRAE
Campus Agro Paris-Saclay
22 place de l'agronomie
91120 Palaiseau
nicolas.jouvin[at]inrae[dot]fr
Academic CV (4/11/2025)
🚲 On sabbatical leave
From May 4, I'll be away from work and my e-mails for 4 months. I'll be back on September 7.
I am a researcher at INRAE in the MIA-Paris laboratory, working in statistics and machine learning. I mainly worked in computational statistics for inference of latent variable models. Recently, I’m also interested in physics-informed machine learning methods and their applications for inverse problems and generative modeling.
From 2020 to 2021, I was a postdoc at Ecole Centrale Lyon working with Yohann De Castro on learning mixture models with sparse regularisation on the space of measures. Prior to that, I completed my PhD on high-dimensional data and graph clustering with discrete latent variable models at Paris 1 Panthéon-Sorbonne University, under the supervision of Pierre Latouche, Charles Bouveyron and Alain Livartowski.
research interests:
- Physics-informed machine learning (PINNs)
- Latent variable models
- Variational inference
- Sparse regularisation
news
| Apr 24, 2026 | On sabbatical (no e-mail) until September 7 |
|---|---|
| Apr 15, 2026 | PIML Day, April 15, @AgroPariTech |
| Apr 14, 2026 | Our PINNs tutorial for the PIMLDay |
| Apr 10, 2026 | Checkout jinns v1.9 |
| Feb 17, 2026 | Slides from my talk at LPSM statistics seminar |