Antonin Raffin
Researcher at German Aerospace Center (DLR)
Bavaria, Germany
Summary
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Rockstar🎓
Top SchoolAntonin Raffin is a researcher based in Bavaria, Germany with 10 years of experience at the intersection of robotics and machine learning, specializing in reinforcement learning. He combines hands-on engineering and research—implementing core RL algorithms like TD3 and TQC in PyTorch and contributing to Stable-Baselines3 and its contribs while maintaining a training zoo of 100+ pre-trained agents. His open-source work spans foundational projects such as OpenAI Gym and Bullet Physics, where he improved testing, added environment integrations and pybullet examples to make simulations more reproducible. Antonin also bridges robotics theory and practice, adding Bezier-based path planning and controller improvements to PythonRobotics and integrating Optuna-based hyperparameter optimization for RL workflows. Known for full-stack contributions, strong test coverage and clear documentation, he focuses on making research code robust and ready for real-world robot simulation.
10 years of coding experience
1 year of employment as a software developer
Engineer’s Degree, Robotique et Systèmes Embarqués, Engineer’s Degree, Robotique et Systèmes Embarqués at ENSTA ParisTech - École Nationale Supérieure de Techniques AvancéesDr. rer. nat., Mechatronics, Robotics, and Automation Engineering, Dr. rer. nat., Mechatronics, Robotics, and Automation Engineering at Technical University of MunichClasses préparatoires Aux Lazaristes PCSI - PC*Master’s Degree, M2 Apprentissage, Information et Contenu - Machine Learning, Information and Content, Master’s Degree, M2 Apprentissage, Information et Contenu - Machine Learning, Information and Content at Université Paris-Saclay
French, English, German, Spanish
Github Skills (46)
algorithm10
simulation10
pytorch10
debug10
ppp10
robotics10
documentations10
pytest10
python10
testing10
gymnasium10
simulations10
machine-learning10
reinforcement-learning10
open-ai-gym10
Programming languages (13)
Github contributions (5)
Stable-Baselines-Team/stable-baselines3-contrib
Sep 2020 - Jan 2023
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
Role in this project:
ML Engineer
ML EngineerContributions:17 releases, 156 reviews, 113 commits in 2 years 4 months
Contributions summary:Antonin contributed significantly to the implementation and maintenance of the TQC (Truncated Quantile Critics) algorithm within the Stable-Baselines3-Contrib repository. Their commits include the addition of core TQC components like policies, critic networks, and related scripts. The user was responsible for code cleanup, dependency updates, and improvements to test coverage, demonstrating a focus on integrating a new reinforcement learning algorithm into the project.
contribstable-baselinespybulletmahjonggsde
DLR-RM/stable-baselines3
Sep 2019 - Jan 2023
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Role in this project:Back-end Developer
Back-end DeveloperContributions:23 releases, 855 reviews, 675 commits in 3 years 5 months
Contributions summary:Antonin implemented and initialized TD3 (Twin Delayed Deep Deterministic Policy Gradients) algorithm with PyTorch for reinforcement learning. The implementation involved the creation of a dedicated TD3 class that inherits from the base RL model. This class includes methods for selecting actions, training the critic and actor, and storing the transitions in a replay buffer.
pythonstable-baselinesrobustnessgsdesde
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