Nicolas Renaud
Consultant Quantum & AI at Quantum Application Lab
Amsterdam, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolNicolas Renaud is a Consultant in Quantum & AI with nine years of hands-on experience translating advanced computational science into practical software and organizational strategy. He has led research software engineering teams and technology strategy at the Netherlands eScience Center and now steers quantum and AI initiatives at SURF and the Quantum Application Lab, bridging academic research with industry partners. His background as a postdoc in theoretical and quantum chemistry and a PhD in nanotechnology gives him deep domain expertise in numerical methods, HPC and machine learning for materials and energy research. A pragmatic open-source contributor, he has improved core linear-algebra routines in a C++ eigenvalue library, signaling a focus on correctness and performance in computational kernels. Colleagues rely on him to recruit and mentor top technical talent while turning exploratory research into reproducible, production-ready software. He combines scientific rigor with product-minded delivery to accelerate the real-world impact of quantum computing and AI.
9 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (PhD), Nanotechnology, Doctor of Philosophy (PhD), Nanotechnology at Université Paul Sabatier (Toulouse III)
French, English, Dutch
Github Skills (6)
c-language10
eigen10
cprogramming-language10
linear-algebra10
testing9
headeronly8
Programming languages (8)
Github contributions (5)
yixuan/spectra
Jul 2020 - Jul 2020
A header-only C++ library for large scale eigenvalue problems
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits in 1 day
Contributions summary:Nicolas primarily focused on refactoring and improving orthogonalization algorithms within the C++ library. They introduced a new orthogonalization method, JensWhener, and fixed a bug related to its implementation. Additionally, the user updated and expanded the testing suite, demonstrating a focus on ensuring the correctness of the linear algebra routines. These contributions show an emphasis on the core computational aspects of the library.
cppeigenvalueeigenvaluesarpacklinear-algebra
NLESC-JCER/Schrodinet
Dec 2019 - May 2023
RBF-NN QMC for potential problem
Contributions:2 releases, 4 PRs, 23 pushes in 3 years 5 months
qmcnearest-neighborsrbfproblemkorean-nlp
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