Abdel-Rahim MEZIDI

Abdel-Rahim Mezidi is a PhD student in the MALICE Inria project-team within the Laboratoire Hubert Curien. His research explores physics-informed machine learning, neural operators, and proximal optimization, with applications in surface engineering and fluid dynamics. He is the principal author of 3 articles (1 preprint and 2 workshop) on contributions related to development of a unified Bregman Proximal viewpoint for neural operators. Abdel-Rahim holds an engineering degree in Computer Science and Networks from Télécom Saint-Étienne, specializing in machine learning and big data. He is also actively involved in teaching graduate-level courses on data analysis, optimization, and scripting languages.
 

ABDEL-RAHIM'S MOTIVATION FOR SCIENTIFIC RESEARCH

"During my final year of engineering school, I specialized in machine learning, which deepened my interest in using AI to address real-world problems. In surface engineering, many challenges arise due to insufficient knowledge of the underlying physics and a lack of available data. This makes it crucial to develop models that are not only efficient and accurate but also interpretable and capable of producing knowledge for physicists. My research on neural operators aims to provide a new perspective on these models by using an optimization framework, helping us better understand their training. This work allows me to explore new ideas while contributing to both machine learning theory and practical applications."