Michelle Girvan

Michelle Girvan is a Professor in the Department of Physics at the University of Maryland, College Park (UMD), with affiliations in the Institute for Physical Science and Technology and the Institute for Research in Electronics and Applied Physics. Her research focuses on network science applications in biological, social, and technological systems, integrating machine learning and nonlinear dynamics. She holds a B.S. from MIT (1999) and a Ph.D. from Cornell University (2003), followed by a postdoctoral fellowship at the Santa Fe Institute. Notable awards include the UMD Distinguished Scholar-Teacher (2022) and Fellow of the American Physical Society.

Her work spans interdisciplinary topics such as information cascades, epidemiology, and genetic regulatory networks. Recent projects emphasize hybrid forecasting models combining machine learning with knowledge-based systems. Girvan leads the Girvan Networks Lab, advising over 20 graduate students and postdocs. She teaches courses like Physics 165 (Programming for Physical Sciences) and Physics 615 (Nonlinear Dynamics). Her $3M NSF grant supports training in network biology, leveraging computational methods to address complex systems challenges.

Scientific contributions include studies on reservoir computing for dynamical systems prediction, jet lag asymmetry modeling, and network robustness in neuronal systems. She serves on the Santa Fe Institute's External Faculty and Science Steering Committee, promoting interdisciplinary collaboration in network science.