|Tsinghua University Pao-Lu Hsu Distinguished Lecture|
|Instructor：||David Aldous [University of California, Berkeley]|
|Place：||Lecture hall, Floor 3, Jin Chun Yuan West Building|
Lecture 1: Interacting particle systems as stochastic social dynamics
Abstract: The style of mathematical models known to probabilists as Interacting Particle Systems and exemplified by the Voter, Exclusion and Contact processes have found use in many academic disciplines. Often the underlying conceptual picture is of a social network, where individuals meet pairwise and update their "state" (opinion, activity etc) in a way depending on the two previous states. This picture motivates a precise general setup we call Finite Markov Information Exchange (FMIE) processes. The talk will briefly describe a few less familiar models (Averaging, Deference, Fashionista) suggested by the social network picture, as well as some more familiar ones.
Lecture 2: The Compulsive Gambler and the Metric Coalescent
Introduction of Speaker:
David Aldous is Professor in the Statistics Dept at U.C. Berkeley, since 1979. He received his Ph.D. from Cambridge University in 1977. He is the author of "Probability Approximations via the Poisson Clumping Heuristic" and (with Jim Fill) of a notorious unfinished online work "Reversible Markov Chains and Random Walks on Graphs". His research in mathematical probability has covered weak convergence, exchangeability, Markov chain mixing times, continuum random trees, stochastic coalescence and spatial random networks. A central theme has been the study of large finite random structures, obtaining asymptotic behavior as the size tends to infinity via consideration of some suitable infinite random structure. He has recently become interested in articulating critically what mathematical probability says about the real world.