Fabien Teytaud
Head Of Data Intelligence
France
Summary
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Rockstar🎓
Top SchoolFabien Teytaud is a Head of Data Intelligence with over a decade of experience bridging academic research and production AI, now leading data and ML strategy at CybelAngel. His expertise centers on black-box and evolutionary optimization, reinforcement learning, Monte-Carlo Tree Search and deep generative models, implemented in Python and C/C++ in Linux environments. A former university maître de conférences and PhD in computer science, he brings rigorous research methods to applied ML problems and team leadership. He is an active contributor to the well-known Nevergrad project, improving evolutionary algorithms and ML benchmarking—an indicator of his commitment to robust, gradient-free optimization for real-world workflows. Unusually for a leader, he combines deep algorithmic work (population-size adaptation, TBPSA refactors) with hands-on benchmark engineering, making him effective at both research and productionization.
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Université Paris Sud (Paris XI)
Github Skills (10)
algorithms10
machine-learning10
benchmark10
benchmarking10
python10
optimization10
keras9
scikit8
scikit-learn8
tensorflow7
Programming languages (2)
Github contributions (5)
facebookresearch/nevergrad
Dec 2019 - Dec 2020
A Python toolbox for performing gradient-free optimization
Role in this project:
ML Engineer
ML EngineerContributions:13 reviews, 11 commits, 12 PRs in 11 months
Contributions summary:Fabien primarily contributes to the development and enhancement of machine learning algorithms and related benchmarks within the nevergrad repository. They implemented and refined various EMNA algorithm versions, including population size adaptation, and refactored the TBPSA algorithm. The user also added new ML datasets and a keras tuning benchmark, demonstrating a focus on improving and expanding the library's capabilities for ML optimization and evaluation.
pythontoolboxgradient-free-optimizationoptimizationpython-toolbox
fteytaud/nevergrad
Dec 2019 - Sep 2023
A Python toolbox for performing gradient-free optimization
Contributions:1 PR, 204 pushes, 24 branches in 3 years 9 months
pythontoolboxgradient-free-optimizationoptimizationpython-toolbox
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