Sylvain Desroziers
Manager I4.0 Exploration
Lagny-sur-Marne, Île-de-France, France
Summary
🤩
Rockstar🎓
Top SchoolSylvain Desroziers is a seasoned AI and data science leader with 10+ years of experience combining applied mathematics, HPC and deep learning to drive digital manufacturing improvements at Michelin. As Manager I4.0 Exploration and Principal Data Scientist, he leads generative AI and advanced robotics initiatives that leverage process data across tire production to boost quality and performance. His background spans research-grade numerical simulation and real-time computer vision, from a PhD in applied mathematics to building parallel C++ platforms and production-ready deep learning solutions. An active open-source contributor, he has helped evolve the popular pytorch/ignite library—improving metrics, type hints and TensorBoard integration—bringing research rigor to engineering practices. Known for bridging academic research and industrial deployment, he also served on ANR scientific evaluation panels, underscoring his ability to assess and steer high-impact R&D.
10 years of coding experience
16 years of employment as a software developer
Ph.D., Applied Mathematics, Ph.D., Applied Mathematics at Université Pierre et Marie CurieMaster, Applied Mathematics, Master, Applied Mathematics at Université Paris Sud (Paris XI)
Github Skills (8)
neural-network10
pytorch10
machine-learning10
deep-learning10
python10
metric10
documentation9
tensorboard9
Programming languages (8)
Github contributions (5)
pytorch/ignite
Mar 2020 - May 2022
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:639 reviews, 87 commits, 228 PRs in 2 years 3 months
Contributions summary:Sylvain contributed to the documentation and implementation of functionality within the `pytorch/ignite` repository, focusing on extending the library's features for training and evaluating neural networks. Key contributions include adding documentation for modules related to engines and metrics, refactoring metric implementations, and addressing type hints to improve code quality. The user also contributed to the integration with tensorboard and updated the codebase to adapt to newer versions of PyTorch and dependencies, demonstrating experience with the underlying technologies and their evolution.
pytorchpythondeep-learninghigh-levelneural-networks
sdesrozis/ignite
Mar 2020 - May 2022
High-level library to help with training neural networks in PyTorch
Contributions:431 pushes, 185 branches in 2 years 3 months
pytorchdeep-learninghigh-levelneural-networksmachine-learning
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