Physics-informed machine learning for composite materials
Ph.D. Assistant at EPFL, Intelligent Maintenance and Operations Systems Lab
I am a Ph.D. candidate at EPFL working in the IMOS Lab led by Prof. Olga Fink. My research is centered on physics-informed machine learning methods for structural health monitoring, damage localization, and surrogate modeling of composite materials. My work connects graph neural networks, finite element simulations, and inverse problems for safer and more reliable engineered systems. Among my research interests are graph neural networks, composite materials, finite element methods, active learning, and inverse problems.
I am a Ph.D. assistant in the IMOS Lab at EPFL, supervised by Prof. Olga Fink. My doctoral work is part of the Horizon Europe Marie Sklodowska-Curie Actions project ASSESS.
Before EPFL, I completed my M.Sc. in Physics at Karlsruhe Institute of Technology, where I worked on machine learning for potential energy surfaces of atomistic systems in the Artificial Intelligence for Materials Sciences group.