Steven N. Evans

University of California, Berkeley

Election Year: 2016
Primary Section: 32, Applied Mathematical Sciences
Secondary Section: 11, Mathematics
Membership Type: Member


Steven Evans is a probabilist working in the theory of stochastic processes and their applications to areas including population genetics, biodemography (evolutionary explanations of aging and senescence), and population dynamics.

Evans grew up in rural Australia and graduated with the University Medal in Statistics from the University of Sydney. He worked for the Commonwealth Banking Corporation of Australia before and after obtaining a PhD from the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. Evans joined the Department of Statistics at the University of California at Berkeley in 1989 following a post-doctoral position at the University of Virginia, and he has held a joint appointment in Mathematics since 1999. He has been a Presidential Young Investigator and a Sloan Fellow. As well as being a member of the National Academy of Sciences, Evans is Fellow of the Institute of Mathematical Statistics and the American Mathematical Society.

Research Interests

Steven Evans has interests that cover a broad cross-section of the mathematical theory of probability and its applications. On the theoretical side, he has contributed to the study of sample path properties of Levy processes and Brownian motion, probability on algebraic structures such polynomials, groups and fields, probability on combinatorial structures such as trees, measure-valued Markov processes, random measures, point processes, coalescing particle systems, spectra and elementary divisors of random matrices, and Doob--Martin compactification theory. Evans' work in applications -- much of it collaborative -- has ranged across phylogenetics (particularly phylogenetic invariants and phylogeny in historical linguistics), biodemography (elucidating the evolutionary basis of aging and senescence using mutation-selection-recombination models), population genetics (inference of natural selection from ancient DNA), metagenomics (methods for displaying the diversity between and within metagenomic samples), mathematical finance (models for default), population dynamics (understanding protected polymorphisms and the evolutionary stability of patch-selection strategies in the presence of spatio-temporal heterogeneity), and astronomy (they dynamics of propellers in the rings of Saturn).

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