Summary
Redouane Lguensat is a Climate Data Scientist in Paris with a decade of experience applying statistical modeling and machine learning to climate modeling and services for developing countries. He combines a PhD in Computer Vision and a strong mathematical background with hands-on postdoctoral work tuning numerical models and inverting remote-sensing missions like SWOT. Currently split between IPSL and IRD, he bridges academic research, editorial work at AI for the Earth Systems, and practical impact through cofounding MoroccoAI. His research blends spatio-temporal data assimilation, Bayesian filtering and analog ensemble ideas to recover dynamics from noisy, incomplete observations—a theme he likens to addressing “inverse problems” in people and data. Comfortable in both theory and applied pipelines, he has repeatedly translated advanced algorithms into mission-driven climate applications. Colleagues value his ability to connect rigorous probabilistic methods with actionable climate services for under-resourced regions.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at Université de Bretagne Occidentale
Doctor of Philosophy (PhD), Computer Vision, Doctor of Philosophy (PhD), Computer Vision at IMT Atlantique
Research Master's degree with highest honour, Image processing, Research Master's degree with highest honour, Image processing at Université de Rennes I
Preparatory classes for the french Grandes écoles, MPSI/MP*, Preparatory classes for the french Grandes écoles, MPSI/MP* at CPGE Mohamed V
Engineer's degree, Information processing systems, Engineer's degree, Information processing systems at Telecom Bretagne
English, French, Arabic, Chinese, amazigh, Spanish