Born in Texas and raised in Minnesota, Peter Mucha moved east to attend college at Cornell University where he majored in Engineering Physics. After a Churchill Scholarship studying 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 UNC-Chapel Hill, where he has served as chair of the Department of Mathematics, the founding chair of the Department of Applied Physical Sciences, and is the current Director of the Chairs Leadership Program at the Institute for the Arts & Humanities.
Mucha’s research includes a variety of topics in the mathematics of networks, including network representations of data, community detection, and modeling dynamics on and of networks. His group’s activities are fundamentally interdisciplinary, applying tools of network analysis and data science in collaborations across the mathematical, physical, life, and social sciences.
Mucha’s 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 Archaeology, Biostatistics, Epidemiology, Finance, Geography, Infectious Diseases, Neuroscience, Pharmacology, Pharmacy, Physics, Political Science, Psychology, Public Policy, Sociology, and Statistics, among others.
Our research group includes postdoctoral scholars, graduate students, and undergraduate researchers working on different aspects of networks and data science, including developments in community detection, network representations of data, modeling network dynamics, and diffusive processes with applications to disease and health behaviors. Our group is diverse and inclusive, supporting each others’ efforts as we work on individual projects and find natural collaborations when opportunities present themselves. Because our work is fundamentally interdisciplinary, we also collaborate with a number of other students and faculty from other departments and universities.