David Aldous (UC Berkeley)
Interacting particle systems as stochastic social dynamics
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,
Compulsive Gambler, Deference, Fashionista) suggested by the social
network picture, as well as the familiar ones.
David Aldous is Professor in the Statistics Dept at U.C. Berkeley, since 1979. He received his Ph.D. from the University of Cambridge in 1977.
His research in 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.
His awards include
the Rollo Davidson Prize and the Loeve Prize.
He is a Fellow of the Institute of Mathematical Statistics, the American Mathematical Society, the Royal Society,
the American Academy of Arts and Sciences, and he is a foreign associate of the National Academy of Sciences.