Mikel Legasa
Postdoctoral Scientist at CNRS
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolMikel Legasa is a postdoctoral climate scientist based in Paris who brings nine years of experience applying machine learning and generative AI to improve climate model resolution and better characterize extremes for local adaptation. Currently on the ESTIMR team at LSCE/CNRS and a member of the TRACCS PC10 steering committee, he focuses on bridging climate science and data-driven methods to deliver actionable, high-resolution climate information. He earned a doctorate in Machine Learning Applied to Climate Change Projections (Cum Laude) and combines a strong mathematical background with hands-on research and teaching experience in data science. Mikel actively translates complex science to broader audiences through school outreach and public talks, and his interests in theatre and rock climbing have sharpened his communication, teamwork, and creative problem-solving skills.
9 years of coding experience
1 year of employment as a software developer
Doctor of Science, Machine Learning Applied to Climate Change Projections, Cum Laude, Doctor of Science, Machine Learning Applied to Climate Change Projections, Cum Laude at Universidad de CantabriaDegree, Mathematics, Degree, Mathematics at Universidad del País Vasco/Euskal Herriko Unibertsitatea
Spanish, Basque, English, French
Github Skills (15)
r-package8
r6
model-validation5
jupyter-notebook4
atlas3
notebook3
svd3
climate-change2
datasets2
workspace2
climate-science2
open-data2
sustainability1
rust1
visualization1
Programming languages (4)
Github contributions (5)
MNLR/RandomForestDist
Mar 2021 - Nov 2022
Contributions:3 releases, 50 commits, 38 pushes in 1 year 8 months
MNLR/rpart
Mar 2021 - Dec 2022
Recursive Partitioning and Regression Trees
Contributions:1 release, 20 pushes, 1 tag in 1 year 8 months
regressionpythonregression-treespartitioningrecursive
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