This talk will discuss an algorithmic approach to the study of dynamical systems on time-varying graphs. Diffusive influence systems have been used to model all sorts of dynamics, from political polarization to firefly, power grid, and heart pacemaker cell synchronization. We review a suite of new techniques for analyzing such systems, including the s-energy, network sequence parsing, multi-agent renormalization, tensor lifts, and message-passing methods.
Bio: Bernard Chazelle is Eugene Higgins Professor of Computer Science at Princeton University, where he has been on the faculty since 1986. His current research focuses on the “algorithmic nature” of living systems. A professor at the Collège de France in Paris in recent years as well as a member of the Institute for Advanced Study in Princeton, he received his Ph.D in computer science from Yale University in 1980. The author of the book, "The Discrepancy Method," he is a fellow of the American Academy of Arts and Sciences, the European Academy of Sciences, and the recipients of three Best-Paper awards from SIAM.