Research · Engineering · Building products
Machine learning & algorithms
I'm a final-year Data Science & AI engineering student at ESIEE Paris. I work on algorithms and applied machine learning, from topological image segmentation at LIGM–CNRS to customer-facing AI workflows at Reaply.
Available from 8 February 2027, with flexibility to early March. Open to international opportunities.
I’m particularly interested in reliable learning systems, computer vision and reinforcement learning: how to build them, evaluate them and understand where they fail.
Selected work
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morseq — Topological image segmentation
A single-pass basin-labeling algorithm, linear in the incidence structure. A pure-Python implementation with 623 automated tests, including checks of cut consistency and closure invariants.
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Reaply — AI for multi-location businesses
A live product for Google review analysis, response generation and cross-location benchmarking. Built around customer needs, with a footprint of 300+ locations.
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Toxic gas identification — 18th out of 238
Predicted 23 alarm levels from 13 sensor signals using tree ensembles in the Bertin Technologies challenge.
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UniSpace — Campus room booking
Flutter and Firebase application for room availability and reservations. Jury's Coup de Cœur award at ESIEE Paris's Jour des Projets.
More projects and technical details →Request my CV
Background
ESIEE Paris, Diplôme d’Ingénieur — expected September 2027. Ranked 1st/41 in AI & Deep Learning (18.19/20), and 1st in Data Mining R and DevOps Data (19/20 each). Exchange semester at the University of Bologna; additional physics coursework at Sorbonne Université.
I also participated in the MIT Rising Scholar Program in 2026. Outside technical work, I tutor first-year students and serve as Secretary-General of Jeunes Français de l’Étranger.