Yann Planton is a research fellow and data scientist with eight-plus years translating climate science into robust tools and actionable insights, including a lead-developed Python package used by the U.S. DoE and IPCC. He has coauthored 10 papers (one in Nature, one in Science), earned 1200+ citations with a Web of Science Highly Cited paper, and collaborated with over 150 researchers across 50+ institutes. His work blends statistical methods, machine learning, and large-scale model analysis—he led evaluations of 3,500+ climate simulations and reduced model-evaluation complexity by 77% through dimensionality techniques. He has a track record of turning puzzling physical questions into testable experiments, for example explaining asymmetries in El Niño/La Niña predictability, and he applies those insights to improve regional projections and adaptation strategies. Based in Paris and trained in ocean-atmosphere sciences (PhD), he bridges academic rigor and production-ready software that informs policy-grade assessments.
8 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Environmental Fluid Mechanics, Master of Science - MS, Environmental Fluid Mechanics at Université Grenoble Alpes
Doctor of Philosophy - PhD, Ocean, Atmosphere, and Land Surface, Doctor of Philosophy - PhD, Ocean, Atmosphere, and Land Surface at Université Paul Sabatier (Toulouse III)
Contributions:2 releases, 125 pushes, 1 branch in 8 months
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