Conference ID: 997-497-59590
A fascinating aspect of collective dynamics is the self-organization of small-scales and their emergence as higher-order patterns——clusters, flocks, tissues, parties. The emergence of different patterns can be described in terms of few fundamental “rules of interactions”. I will discuss recent results of the large-time, large-crowd dynamics, driven by anticipation that tend to align the crowd, and augmented by other pairwise interactions that keep the crowd together while preventing over-crowding. In particular, I address the question how short-range interactions lead to the emergence of long-range patterns, comparing different rules of interactions based on geometric vs. topological neighborhoods.
Eitan Tadmor is a Distinguished University Professor at the University of Maryland, College Park. He received his Ph.D. from Tel Aviv University in 1979 and began his scientific career in CalTech, 1980-1982. He held professorship positions at Tel-Aviv University, 1983-1998, and at UCLA - where he co-founded IPAM in 1999-2001. Tadmor was the Director of CSCAMM in Maryland, 2002-2016, and a Senior Fellow in the Institute for Theoretical Studies at ETH-Zurich 2016-2017. He was the PI of an NSF Focus Research Group on “Kinetic Description of Multiscale Phenomena”, 2008-2012, and the NSF research network Ki-Net, 2012-2020.
Tadmor delivered an invited address at the 2002 ICM in Beijing, the 2014 SIAM address in Joint Mathematical Meeting, the 2016 Leçons Jacques-Louis Lions at UPMC, Paris VI, and 2019 ICIAM invited address in Valencia. In 2015 he was awarded the SIAM-ETH Henrici prize for “fundamental contributions to the applied and numerical analysis”.
Tadmor’s primary research interests include the interplay between analytical theories and computational aspects of time-dependent problems, with applications to shock waves, kinetic transport, incompressible flows, image processing and self-organized dynamics. He is credited with fundamental contributions associated with the notions of high-resolution central schemes, entropy stability, spectral viscosity methods, kinetic description of conservation laws, hierarchical description of images, and in recent years, he is leading an interdisciplinary research program in modeling and analysis of collective dynamics with applications to flocking and opinion dynamics.