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Peter Mucha

Professor of Mathematics and Applied Physical Sciences
Chapman Hall 425
mucha@unc.edu
919-962-2568

Research Interest:
Interdisciplinary Approach to Data Science Focused on Networks and Network Representations

        

Professional Background

Peter Mucha is a Professor of Mathematics and Applied Physical Sciences at the University of North Carolina at Chapel Hill. He grew up in Minnesota, moving east to attend college at Cornell University where he majored in Engineering Physics. After taking a Churchill Scholarship to study in the Cavendish Laboratory at Cambridge with an M.Phil. in Physics, he returned to the States to continue his studies at Princeton with an M.A. and Ph.D. in Applied and Computational Mathematics. Following a postdoctoral instructorship in applied mathematics at MIT, and a tenure-track assistant professorship in Mathematics at Georgia Tech, he moved to Chapel Hill to join the Department of Mathematics and the Institute for Advanced Materials, now folded into the new Department of Applied Physical Sciences, at UNC. His research includes a variety of topics in network science, including developments in community detection, network representations of data, and modeling dynamics on and of networks. His group activities are fundamentally interdisciplinary, with collaborations on varied topics across the mathematical, physical, life, and social sciences.

Research Synopsis

My research group embraces an interdisciplinary approach to data science focused on networks and network representations. We use mathematical models and statistical principles to develop and apply computational tools for the study of real-world data, working in close collaboration with domain science experts. With “nodes” representing objects of interest and “edges” that connect the nodes representing relationships or similarities, the concept of a network can be flexibly used across many applications.

Most people are familiar with the concept of a network in terms of hyperlinked web pages or online social networks, and online networks are indeed an area of broad interest, including some of our own work. But networks can be successfully applied to a much wider variety of connected systems, and our group’s collaborations have included researchers in departments of Archeology, Biostatistics, Epidemiology, Finance, Geography, Infectious Diseases, Neuroscience, Pharmacology, Pharmacy, Physics, Political Science, Psychology, Public Policy, Sociology, and Statistics, among others.

My research group currently includes postdoctoral scholars Clara Granell, Saray Shai and Dane Taylor; graduate students Sam Heroy, co-advised with Greg Forest, Jessime Kirk, in Mauro Calabrese’s lab, Hsuan-Wei “Wayne” Lee, Natalie Stanley and William Weir; and undergraduates Daniel Cantwell, Scott Emmons, Ryan Gibson, Austen Kelly, Nic Larsen, Zichao Li, Alex Touzov, Sean Xiao and Eileah Zugger.

Each student is working on some aspect of the study of networks, including developments in community detection, network representations of data, modeling network dynamics, model interactions in networked materials, and diffusive processes with applications to disease and health behaviors. Our group activities are fundamentally collaborative, with a variety of ongoing collaborations with students and faculty from other departments and universities.