Bio
I am currently a PhD student in Computer Science at the
Laboratory of Algorithmics, Complexity, and Logic (LACL)
at Université Paris-Est Créteil Val de Marne.
My PhD thesis is titled: Machine Learning for Continuous Systems Based on Probabilistic Approximations.
I began my PhD on October 1, 2024, under the supervision of Nihal Pekergin, Benoît Barbot, and Adrien Le Coënt.
Before that, I completed a Master’s degree in Mathematics, Modeling, and Statistical Learning (MMAS) at Université Paris Cité. During this time, I also completed a six-month internship at Dassault Systèmes, where I worked on deep Gaussian processes for multi-fidelity simulation.
Research Interests
- Markov chains and Bayesian networks.
- Differential equations (ODE, PDE, SDE).
- Parameter estimation and uncertainty quantification.
- Exact and approximate model reduction methods.
- Sensitivity analysis.
- Quasi-Monte Carlo and deterministic sampling techniques.
About this Website
This website was designed and developed by me. The graph background was generated with NebulaNet. Header background by Valeria Nikitina on Unsplash. Profile picture by Mila Okta Safitri on Unsplash.
Contact
You can find my e-mail adress in my CV.
Copyright
© 2026 Olivier Bouët-Willaumez. All rights reserved.