Johan Mabille is a software architect and Technical Director with 12+ years delivering high-performance C++ systems for investment banking and scientific computing. He blends deep expertise in numerical algorithms, template metaprogramming and SIMD vectorization (SSE/AVX) with hands-on experience in multithreaded design and large-scale refactoring of pricing libraries. An active open-source maintainer and Project Jupyter Steering Council member, he co-authors xtensor/ xsimd and contributed substantial functionality to widely used projects like pybind11 and xeus-cling, improving C++/Python interoperability and Jupyter C++ kernel robustness. He teaches C++ at École Polytechnique, runs a consultancy, and has repeatedly delivered 10–20× performance gains in production quant libraries. Comfortable across backend and full-stack open-source work (including JupyterLab and bqplot), he combines production-grade engineering with developer tooling and reproducible computing interests.
C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, AVX512, NEON, SVE, WebAssembly, VSX, RISC-V))
Role in this project:
Back-end Developer & Library Maintainer
Contributions:117 reviews, 833 commits, 655 PRs in 7 years
Contributions summary:Johan's commits focus on developing a low-level SIMD (Single Instruction, Multiple Data) library in C++. Their contributions primarily involve implementing and optimizing functions for mathematical operations, as well as data transfer instructions, specifically leveraging SIMD intrinsics. The user has worked on incorporating support for various instruction sets, including SSE and AVX, and testing the implemented functionality. Furthermore, the user has also added the ability to use the library with complex numbers.
Contributions:201 reviews, 1744 commits, 1628 PRs in 6 years 7 months
Contributions summary:Johan contributed to the core logic of the C++ tensors with broadcasting and lazy computing library. Their commits focused on extending the xcontainer and xexpression system, including implementing new functions and features. They also worked on integrating the dynamic view system to achieve enhanced features, and included fixes and optimizations for iterators and access functions.
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