Summary
Valentin Resseguier is an applied mathematics researcher with a PhD in signal processing and geophysical fluid dynamics and over a decade of experience translating stochastic modeling and uncertainty quantification into industrial R&D. He has driven research-to-product efforts at Scalian and now INRAE, working across machine learning, NLP, wave simulation and stochastic parametrizations for fluid dynamics. His academic work includes randomized models for ocean currents and stochastic subgrid parametrization, and he has practical experience building observers and control prototypes for downhole pump systems. Comfortable in MATLAB and statistical tools, he blends rigorous probabilistic modeling with hands-on simulation engineering and teaching. A less obvious strength is his international research background—from INRIA/IFREMER to postdocs in the US and Argentina—giving him a broad perspective on applied modelling challenges.
10 years of coding experience
Master's degree, Engineering, 70, Master's degree, Engineering, 70 at École Supérieure d'Électricité
Master's degree, Signal processing and Statistics, Master's degree, Signal processing and Statistics at University Paris XI
Doctor of Philosophy (PhD), Signal Processing, Geophysical fluid dyanmics, Stochastic Differential Equations, Doctor of Philosophy (PhD), Signal Processing, Geophysical fluid dyanmics, Stochastic Differential Equations at INRIA / IFREMER
Bachelor's degree, Mathematics, Physics and Chemistry, Bachelor's degree, Mathematics, Physics and Chemistry at Preparatory Course - Lycée Buffon
English, French, Russian