Marco Grassia

I study complex networks using methods from Network Science and Machine Learning. My current work focuses especially on Graph Machine Learning and model interpretability, including understanding which parts of a network influence a model’s prediction and how reliably such explanations capture its behaviour. I also work on network robustness and dismantling, combinatorial problems on networks, and applications in neuroscience, astrophysics, and econophysics.

Across different projects and collaborations, my work has followed three recurring threads.