About
PhD student at Inria, Rennes. Previously machine learning engineering at Sudo Group and research placements at the CNRS.
I am a PhD student at Inria, Rennes, working on artificial intelligence for the mechanical durability of systems subjected to severe vibratory loads. The thesis is funded by the Agence de l’innovation de défense and runs as a consortium between the DGA, the University of Angers and the University of Rennes.
Before this I read a MSc in Machine Learning at the Université de Lille, graduating with honours, after a year of the Complex Systems Engineering master’s at the UTC in Compiègne and a computer science bachelor’s in the CMI programme at the Université Bretagne Sud.
Alongside the master’s I spent a year as an ML engineer at Sudo Group in Lille, in the R&D team, working on machine learning for cloud cost optimisation. Earlier I held two research placements at the CNRS, on semantic segmentation of ultra-high-resolution drone imagery and on evaluating a 3D point cloud classification algorithm against urban LiDAR data, and an engineering internship at Accenture Technology in Nantes.
I teach machine learning to third-year bachelor students at the UCO in Angers — ten hours of lectures and lab sessions, from the supervised learning pipeline through to convolutional networks and variational auto-encoders.
I work on artificial intelligence, machine learning and mathematics applied to concrete problems. Lately that has included extreme value statistics.
I also write about AI regulation: a proposal for a global regulation office, and a follow-up on why binding rules for frontier labs are overdue and who should be in the room when they are written.
Outside the thesis I follow how quantitative finance and signal analysis intersect with geopolitics — what the shorter notes tend to be about.
Contact
Rennes, France.