The Department of Mechanical & Aerospace Engineering Stanford S. and Beverly P. Penner Distinguished Lectures

Computing with Uncertainty Alexandre Chorin Lawrence Berkeley National Laboratory Department of Mathematics , Berkeley Monday, April 7, 2014 4:00 p.m.-5:00 p.m. CMRR Auditorium, UCSD

ABSTRACT There are many problems in science and engineering where one needs to estimate the solution of uncertain equations with uncertain or incomplete data. Some examples will be presented. In particular, I will consider the extraction of model parameters from noisy data (e.g., the estimation of diffusion coefficients), inference from uncertain differential equations supplemented by a stream of random data (as in economics, robotics, and weather prediction), and the solution of differential equations with random data (as in uncertainty quantification and model reduction). I will also discuss why predictions fail and the conditions under which such problems can be solved.

BIO Alexandre Chorin is a UC Berkeley professor of mathematics and a Senior Faculty Scientist in the Mathematics Group. He received his Ph.D. from the Courant Institute of Mathematics at in 1966, becoming an associate professor in 1971 before joining the Berkeley faculty in 1972. He was Head of the LBNL Mathematics Department from 1986-1985. Chorin's awards include the National Academy of Sciences award in applied mathematics and numerical analysis, the Wiener prize of the American Mathematical Society, and the Lagrange prize of the International Council on Applied Mathematics. Chorin is known for his contributions to computational fluid mechanics, turbulence theory, and computational statistics, including the invention of the ubiquitous projection method for modeling incompressible fluids and the random vortex method for computing turbulent flow.

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