Alice Patania

Alice Patania is an Assistant Professor in the Department of Mathematics and Statistics at the University of Vermont. She holds a PhD in Applied Mathematics from Politecnico di Torino (2017), an M.Sc. and B.Sc. in Mathematics from Università di Torino (2013 and 2010). Her research focuses on computational topology and its applications to complex systems, particularly brain and social networks. She is the Principal Investigator of an NIH R21 grant on integrative predictive modeling of Alzheimer’s disease, combining genomics and neuroimaging data.

Education:

• PhD in Applied Mathematics, Politecnico di Torino (2017)
• M.Sc. Mathematics, Università di Torino (2013)
• B.Sc. Mathematics, Università di Torino (2010)

Research interests include topological data analysis (TDA), network neuroscience, and higher-order network modeling. Her work bridges abstract mathematics with applied problems in neuroscience and medicine. Notable contributions include topological gene-expression networks for brain anatomy/function analysis and simplicial configuration models for network sampling.

Recent publications emphasize Alzheimer’s disease modeling, neural network dynamics, and algorithmic advancements in TDA. She is an inaugural member of the Vermont Complex Systems Center (VCSC), contributing to interdisciplinary research collaborations.

Teaching includes courses on Topology, Algebraic Topology, and Data Science. She actively develops educational materials, such as a Topology course using Munkres and Starbird/Su texts, and a Data Science course inspired by Berkeley’s curriculum.