Published multiple journal papers, such as 'LUNDIsim: model meshes for flow simulation and scientific data compression benchmarks'; submitted several conference papers, including 'Analyse comparative d’algorithmes de restauration en architecture dépliée pour des signaux chromatographiques parcimonieux' (GRETSI 2025), 'Unrolled deep networks for sparse signal restoration in analytical chemistry' (MLSP 2024), etc.; Invited to give a tutorial at CORESA 2021 on the challenges and issues of compression techniques for massive simulation data.
Research Experience
Involved in several collaborative projects: MajIC (E. Chouzenoux), Amidex BIFROST (C. Chaux), TraDe-OPT (H2020 ITN), ANR IA Chair BRIDGEABLE (J.-C. Pesquet), ANR Artificial Intelligence JCJC grant GraphIA (F. Malliaros), ANR BRUIT-FM. Has given talks and tutorials at international conferences.
Background
Research interests include signal processing, image analysis, data science, machine learning, and their applications.
Miscellany
Personal links include blogs, social media accounts, and various academic networking platforms like Google Scholar, GitHub, LinkedIn, etc.