Anatol Rapoport Distinguished University Professor of Complex Systems and Physics
Professor Newman's research is on statistical physics and the theory of complex systems, with a primary focus on networked systems, including social, biological, and computer networks, which are studied using a combination of empirical methods, analysis, and computer simulation. Among other topics, he and his collaborators have worked on mathematical models of network structure, computer algorithms for analyzing network data, and applications of network theory to a wide variety of specific problems, including the spread of disease through human populations and the spread of computer viruses among computers, the patterns of collaboration of scientists and business-people, citation networks of scientific articles and law cases, network navigation algorithms and the design of distributed databases, and the robustness of networks to the failure of their nodes.
Professor Newman also has a research interest in cartography and was, along with collaborators, one of the developers of a new type of map projection or "cartogram" that can be used to represent geographic data by varying the sizes of states, countries, or regions.
Professor Newman is the author of several books, including a recent textbook on network theory and a popular book of cartography.
Network structure from rich but noisy data, M. E. J. Newman, Nature Physics 14, 542-545 (2018)
Structure and inference in annotated networks, M. E. J. Newman and Aaron Clauset, Nature Communications 7, 11863 (2016)
Power-law distributions in empirical data, Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman, SIAM Review 51, 661-703 (2009)
Hierarchical structure and the prediction of missing links in networks, A. Clauset, C. Moore, and M. E. J. Newman, Nature 453, 98–101 (2008)
Modularity and community structure in networks, M. E. J. Newman, Proc. Natl. Acad. Sci. USA 103, 8577-8582 (2006)