Chercheur at Institut de recherche d'Hydro-Québec (Research institute of Hydro-Québec)
Montreal, Quebec, Canada
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Summary
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Senior
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Philippe Roy is a physicist and researcher with 11 years of experience applying advanced statistics, probability and machine learning to climate science and atmospheric extremes. Based in Montreal, he combines a PhD in atmospheric sciences and a Stanford certificate in machine learning to build and deploy data-driven climate tools using Python (TensorFlow, scikit-learn), Julia, Matlab and R. He has led project design, supervision and program development in both academic and applied research settings at Hydro‑Québec, UQAM and Ouranos, translating complex model outputs into actionable indices and scenarios. His work includes developing production software for climate extremes and integrating deep learning methods into regional climate analysis. Known for bridging rigorous theory and practical implementation, he often pairs legacy scientific codes (Fortran, Unix) with modern ML workflows to accelerate research-to-decision timelines.
11 years of coding experience
Baccalauréat, Physique, Baccalauréat, Physique at Université de Montréal
Maîtrise, Sciences de l'Atmosphère, Maîtrise, Sciences de l'Atmosphère at UQAM | Université du Québec à Montréal
Doctorat, Sciences de l'atmosphère, Doctorat, Sciences de l'atmosphère at Université du Québec à Montréal
Machine Learning, Statistics, Certificate, Machine Learning, Statistics, Certificate at Stanford University
Contributions:113 commits, 49 PRs, 124 pushes in 1 year 3 months
geodatapythonplotting-libraryplottingjulia
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