Antoine Prouvost is a Scientific Software Engineer and mathematician with 10 years of experience applying machine learning, operations research, and backend engineering to real-world, large-scale systems. He builds robust C++/Python infrastructure—most notably as a core maintainer of the fast, cross-platform Mamba package manager—and contributes to high-performance libraries like xtensor and PySCIPOpt. His work spans research-grade ML and combinatorial optimization (PhD-level) to production data platforms, including a realtime analytics product he helped architect as CTO using Rust, Polars and React. Comfortable across big-data architectures, solver internals and distributed tooling, he often bridges theoretical advances and practical tooling for reproducible scientific workflows. Based in Paris, he pairs academic rigor from Mila/École Polytechnique with hands-on open-source leadership in widely used developer ecosystems.
10 years of coding experience
8 years of employment as a software developer
Mathematics and Physics, Mathematics and Physics at Lycee Blaise Pascal Orsay
Doctor of Philosophy - PhD, Machine Learning and Combinatorial Optimization, Doctor of Philosophy - PhD, Machine Learning and Combinatorial Optimization at École Polytechnique de Montréal
Ingénieur de l'École polytechnique (M.Sc), Applied Mathematics, Computer Science, Ingénieur de l'École polytechnique (M.Sc), Applied Mathematics, Computer Science at École Polytechnique
Contributions:353 reviews, 125 commits, 509 PRs in 1 year 5 months
Contributions summary:Antoine primarily focused on enhancing the Mamba package manager. They made improvements to error messages, added features for dependency management, and refactored components. Their contributions included improvements related to channel management, codebase modularization, and various internal API functions, indicating a strong involvement in the core functionality of the project.
Contributions:47 reviews, 48 commits, 24 PRs in 2 years 10 months
Contributions summary:Antoine primarily contributed to the `xtensor` repository by implementing and refining features related to random number generation and tensor operations. They added new functionalities such as weighted choice with and without replacement, and they improved the existing weighted random sampling implementation. Furthermore, they addressed documentation issues by fixing typos and adding cross-references, thereby improving the overall usability of the library. They also replaced `XTENSOR_THROW` with `XTENSOR_ASSERT` in `xt::random::choice` and refactored code for efficiency.
cppmpinumpypython-bindingsc-plus-plus
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Antoine Prouvost - Scientific Software Engineer at QuantStack