Karel Dumon
Portfolio Manager at Photonics Research Group (Ghent University - imec)
Belgium
Summary
👤
Senior🎓
Top SchoolKarel Dumon is a portfolio manager and R&D leader with nine years of experience applying physics, machine learning and software engineering to quantum computing, alternative computing and photonics. He blends research training—summa cum laude in Engineering Physics and atomistic simulation experience—with startup grit as co-founder and former Head of Software at Miraex. At imec and Ghent University he now steers projects and operations for quantum communications and the BeQCI photonics initiative, translating deep technical concepts into funded programs and tangible roadmaps. His background in strategy consulting and high-throughput quantum simulations gives him a rare combination of commercial sense and first-principles modeling. Colleagues know him for moving fluidly between hands-on ML/quantum tool development and high-level portfolio strategy. Based in Belgium, he is motivated by using the mathematical language of nature to build technology for a better tomorrow.
9 years of coding experience
11 years of employment as a software developer
Bachelor & Master of Science (MS), Engineering Physics, Summa Cum Laude, Bachelor & Master of Science (MS), Engineering Physics, Summa Cum Laude at Ghent UniversityCDL Toronto - Quantum Stream, CDL Toronto - Quantum Stream at Creative Destruction LabSummer School on Atomistic Simulation Techniques, Summer School on Atomistic Simulation Techniques at Scuola Internazionale Superiore di Studi Avanzati di Trieste
Dutch, English, French, German
Stackoverflow
755reputation
59kreached
7answers
4questions
Github Skills (50)
pytorch10
python10
data-science10
machine-learning10
deep-learning10
tensorflow10
jax9
neural-network8
chainer7
quantum-chemistry7
placement7
quadratic7
quantum-computing6
keras6
lstm6
Programming languages (4)
Github contributions (5)
BoschSamuel/QizGloria
Sep 2019 - Oct 2020
Contributions:6 commits, 16 pushes, 1 branch in 1 year
dumkar/learning-to-learn-qnn
Jul 2019 - Aug 2019
Learning-to-learn for QNNs: learning few-shot optimization of quantum neural networks with classical neural networks
Contributions:10 commits, 1 PR, 3 pushes in 1 month
quantum-computingdeep-learningoptimizationneural-networksneural-network
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