Welcome to my personnal webpage !

I am a machine learning researcher interested in the development and translation of new computational methods to solve healthcare challenges.

I did my PhD at Institut Curie, in the SysBio and the LITO laboratories, under the supervision of Emmanuel Barillot and Irène Buvat. I worked on multimodal machine learning approaches to predict immunotherapy outcome for metastatic non-small cell lung cancer (NSCLC) patients (link to my thesis).

Before that, I graduated from Ecole polytechnique. I have a master’s degree in applied mathematics from Ecole polytechnique, and a master’s degree in mathematics, vision, and learning (master MVA) from ENS Paris-Saclay.

I am currently looking for a postdoctoral position in machine learning applied to biomedical questions. Do not hesitate to reach out !

News

• January 12, 2025 - Our paper about the multimodal prediction of immunotherapy outcome in lung cancer has just been published in Nature Communications (article, available data, available code).
• November 12, 2024 - We have just released the new versions of our GitHub repositories multipit and deep-multipit that contain Python tools for multimodal prediction and codes to reproduce the experiments from our paper currently available on medRxiv.
• June 28, 2024 - We have just released our new preprint (main results of my PhD research) entitled Integration of clinical, pathological, radiological, and transcriptomic data improves the prediction of first-line immunotherapy outcome in metastatic non-small cell lung cancer. Check it out on medRxiv !
• May 31, 2024 - I successfully defended my thesis, with a jury composed of Chloé-Agathe Azencott, Lodewyk Wessels, John Prior, Fátima Al-Shahrour, Julia Schnabel, Emmanuel Barillot, and Irène Buvat.
• May 22, 2024 - Our paper RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models was accepted for publication in the Journal of Nuclear Medicine. Check it out here !