About Me

I am a research master’s student in applied maths and machine learning at the MVA master (“Mathématiques, Vision, Apprentissage”) at the ENS Paris-Saclay, as part of a double degree program with my home engineering school Télécom Paris (part of Institut Polytechnique de Paris).

I have two major research experiences:

• One-year research track supervised by Enzo Tartaglione on bias amplification by diffusion models during the first year of my master’s studies, which led to a first-author publication in the Winter Conference on Applications of Computer Vision 2026 (main track).
• A six-month research internship at KU Leuven during my gap year, where I worked with Dmytro Rizdvanetskyi and Pavlo Lutsik on cell type deconvolution from DNA methylation data. We developed a data-driven soft labeling scheme and a state-of-the-art deep learning framework for read-level cell type deconvolution scaling to 39 cell types. Our paper was accepted to NeurIPS 2026 (main track).

I am currently interested in fundamental or applied research in machine learning / applied mathematics in fields with potential applications in biology, healthcare, chemistry and physics. I am looking for a 6-month final-year research internship in these areas starting in April 2027, preferably leading to a PhD.