Structure and Function in Complex Networks
Many systems of interest in science and engineering can be represented as networks: the Internet, the power grid, transportation networks, metabolic networks, ecological networks, and social networks are just a few of the many well studied examples. This talk will give an overview, with illustrative examples, of methods for analyzing and understanding the structure of these complex objects, using spectral and inference methods among others, and the connections between the structure of networks and the behavior or performance of the systems they represent.
Mark Newman received his PhD in physics from the University of Oxford in 1991 and conducted postdoctoral research at Cornell before taking a position at the Santa Fe Institute, a think-tank in New Mexico known for its work on the theory of complex systems. He left Santa Fe in 2002 for the University of Michigan where he is currently the Anatol Rapoport Distinguished University Professor of Physics and a professor in the Center for the Study of Complex Systems. Among other honors, Professor Newman is a Fellow of the AAAS, a Fellow of the American Physical Society, and was the winner of the 2014 Lagrange Prize, the biggest international prize for research in complex systems. His research is in statistical physics and combines traditional ideas such as percolation theory, disordered systems, and Monte Carlo methods, with nontraditional applications, particularly to networked systems such as social and computer networks. He is the author of over 150 scientific publications and seven books, including "Networks", an introduction to the field of network theory, and "The Atlas of the Real World", a popular book on cartography.