Marc Lelarge
Research Faculty at Inria
Paris, Ile-de-France
Summary
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Rockstar🎓
Top SchoolMarc Lelarge is a research faculty at Inria and associate professor with eight years of focused experience at the nexus of mathematical reasoning and AI, blending deep expertise in applied probability, random graphs and combinatorial optimization with practical work on theorem proving, code automation, graph-based deep learning and physics-informed ML. He teaches deep learning across top French institutions and maintains hands-on ML engineering credentials—evidenced by notebook contributions implementing CNNs and core modules for image experiments. A serial academic entrepreneur, he co-founded eOnsight while continuing research and courses at ENS and formerly École Polytechnique. Marc’s profile combines rigorous PhD-level mathematics with production-minded coding, making him adept at turning formal theory into reproducible experiments and tools.
8 years of coding experience
6 years of employment as a software developer
PhD Applied Mathematics, PhD Applied Mathematics at École PolytechniqueEngineer’s Degree, Engineer’s Degree at Télécom ParisMaster’s Degree Statistiques mathématiques et probabilités, Master’s Degree Statistiques mathématiques et probabilités at Pierre and Marie Curie University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
mask-rcnn10
faster-rcnn10
pytorch10
machine-learning10
deep-learning10
image-classification10
python9
Programming languages (7)
Github contributions (5)
dataflowr/notebooks
Sep 2018 - Jan 2023
code for deep learning courses
Role in this project:
ML Engineer
ML EngineerContributions:320 commits, 9 PRs, 384 pushes in 4 years 5 months
Contributions summary:Marc's commits primarily focused on implementing and developing code for a deep learning project within the specified repository. The changes show the user's involvement in processing image data, training a Convolutional Neural Network (CNN), and implementing core modules such as the ReLU activation, indicating their involvement in the model architecture and training procedures. The commits are linked to a dogs vs cats classification problem, which suggests a focus on implementing and running experiments on image data.
deep-learningpytorch
mlelarge/dataflowr-slides
Nov 2018 - May 2020
slides for deep learning courses
Contributions:56 commits, 2 PRs, 53 pushes in 1 year 6 months
deep-learning
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