Clarissa is a postdoctoral fellow in Applied Mathematics, whose interest lies at the intersection between Statistical Physics and Machine Learning. She aims to develop simple theoretical models to explain complex behaviours of learning algorithms and biologically inspired neural networks. Before joining the Pehlevan group, she was a PhD Student at Politecnico of Turin, where she worked on geometric loss landscape characterization and how structural phase transitions affect algorithmic performance.