Robin Dupont is a research engineer with a PhD from Sorbonne Université and a decade of experience applying deep learning to real-world systems, from predictive maintenance at Air France to deploying pruned vision models on 200k smart cameras at Netatmo. He specializes in neural network compression, pruning and sparsity, has published and open-sourced PyTorch implementations of state‑of‑the‑art techniques, and ran large-scale training pipelines on Europe’s Jean-Zay cluster. Now working on AI and algorithms for cold-atoms quantum computing at Pasqal, he bridges academic rigor and industrial deployment, routinely mentoring interns and coordinating cross‑disciplinary teams. Outside of research, he channels his hands-on curiosity into home automation and DIY projects, reflecting a pragmatic focus on privacy-conscious, edge-capable ML solutions.
9 years of coding experience
3 years of employment as a software developer
Deep Learning Mooc by Andrew Ng, Deep Learning Mooc by Andrew Ng at Coursera
Master of Science (MSc), Communications and Signal Processing, Master of Science (MSc), Communications and Signal Processing at Imperial College London
Doctor of Philosophy - PhD, Deep Learning, Neural Network Compression, Doctor of Philosophy - PhD, Deep Learning, Neural Network Compression at Sorbonne Universités
Electrical & Electronics Engineering, Visiting Student, Electrical & Electronics Engineering, Visiting Student at The University of Edinburgh
Master of Science (MSc) in Engineering, Data Science & Big Data, Master of Science (MSc) in Engineering, Data Science & Big Data at Ecole nationale supérieure des Mines de Saint-Etienne
Contributions:9 releases, 27 commits, 8 PRs in 4 months
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