Lorenzo Di Fruscia

I received both my bachelor's and my master's degree in physics from Sapienza University of Rome, with a main focus on complex systems, statistical mechanics, soft matter and artificial intelligence.
During my master's thesis I explored how geometric and physics-informed deep learning can be applied to replace mesh-based simulations in fluid dynamics, and I continued working on similar topics at the National Research Council of Italy (CNR).
In early 2024, I joined the lab as a PhD candidate under the supervision of Prof. Jana Weber, to work on interdisciplinary research in the broad field of molecular machine learning. My main interests revolve around graph representation learning, network science, structural biology and social dynamics. Whether it's modeling human interactions or understanding emergent phenomena in molecules and biological systems, these subjects drive my curiosity.