Sofia Imperatore

Sofia Imperatore is a mathematician by training with a BSc (2017), MSc (2020), and PhD (2024) in Applied Mathematics from the University of Florence, Italy. During her PhD, she focused on geometric deep learning, combining free-form geometric models with data-driven systems, as well as deep-geometric generative models. After her PhD, she undertook a researcher position at CNR in Pavia, Italy, working on uncertainty quantification via sparse grid surrogate models. In her current role as a Postdoctoral Research Fellow in the Molecular Machine Learning group, she focuses on developing deep protein representations enriched with geometric information for drug discovery.