Thierry Guillemot
Ingénieur Recherche En Machine Learning at ARIADNEXT
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolThierry Guillemot is a research engineer in machine learning based in Paris with a decade of experience building Python ML tooling and modern web applications using ES6 and React. He holds a PhD in 3D and image processing and has a strong academic-to-industry trajectory, contributing to medical-data sharing with blockchain and sleep-disorder studies at École Polytechnique. Thierry is a notable open-source contributor to scikit-learn, where he implemented and refactored the widely used GaussianMixture class, demonstrating deep expertise in probabilistic models and library-quality engineering. At ARIADNEXT he applies this research-led rigor to production ML systems, blending algorithmic innovation with practical deployments. Colleagues describe him as someone who bridges rigorous research, clean code, and community-focused documentation and teaching.
10 years of coding experience
5 years of employment as a software developer
Master's degree, Mathematics, Vision and Algorithm, Master's degree, Mathematics, Vision and Algorithm at Ecole normale supérieureBachelor's degree, Electronics, Electrotechnics and Automatics, Bachelor's degree, Electronics, Electrotechnics and Automatics at Université Paul Sabatier (Toulouse III)PhD, 3D and Image Processing, PhD, 3D and Image Processing at Telecom ParisTech
French, English, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
scikit10
machine-learning10
python10
data-science10
scikit-learn10
testing9
statistics9
Programming languages (6)
Github contributions (5)
scikit-learn/scikit-learn
Apr 2016 - Feb 2017
scikit-learn: machine learning in Python
Role in this project:
Data Scientist
Data ScientistContributions:20 commits, 28 PRs, 691 comments in 10 months
Contributions summary:Thierry made significant contributions to the `scikit-learn` library, focusing on the `GaussianMixture` class. They implemented the new `GaussianMixture` class, deprecated the old `GMM` class, and modified the GaussianMixture class. This included refactoring code, correcting tests, addressing issues, and integrating new features and parameters. They also worked on fixing and testing existing functionalities.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
tguillemot/scikit-learn
Feb 2016 - Jun 2017
scikit-learn: machine learning in Python
Contributions:310 pushes, 42 branches in 1 year 4 months
pythondata-sciencelearn-machine-learningsklearnneural-networks
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