External Professor, Science Steering Committee
Michelle Girvan's research combines methods from statistical mechanics, dynamical systems, and graph theory to address interdisciplinary, network-related problems. She is interested in both broad theoretical approaches to complex networks as well as specific applications, especially to information cascades, epidemiology, and genetic regulatory networks. Much of her recent work is aimed at the intersection of network science and machine learning.
Girvan received her B.S. in 1999 from the Massachusetts Institute of Technology and her Ph.D. in 2003 from Cornell University. She is a Professor in the Department of Physics at the University of Maryland (UMD). She also has appointments in the Institute for Physical Science and Technology, the Institute for Research in Electronics and Applied Physics, and the Applied Math and Scientific Computing Program.