Summary
Gabriel Gouvine is a Principal R&D Engineer based in Paris with 11 years of experience at the intersection of machine learning, hardware acceleration and combinatorial optimization. He has driven inference acceleration, pruning and quantization for neural-network accelerators and built optimization solvers and decision-support systems across industries from agriculture to semiconductor design. His background spans compiler and VLSI/FPGA toolchains, C++ solver engineering and applied math research, with hands-on roles at Synopsys, Mipsology, LocalSolver, AMD and now Siemens EDA. Trained at École Polytechnique and Télécom Paris, he combines rigorous academic foundations with practical system-level delivery, and a lesser-known strength is translating advanced optimization research into production compilers and FPGA-aware flows.
12 years of coding experience
10 years of employment as a software developer
Engineer's degree (+ Master) Computer Science Electrical Engineering, Engineer's degree (+ Master) Computer Science Electrical Engineering at École Polytechnique
Engineer's degree (+ Master) Electrical engineering and computer networks, Engineer's degree (+ Master) Electrical engineering and computer networks at Télécom Paris
French, English, German, Chinese