Seminars/Colloquia/Invited Talks

Seminars

George Biros

Fast Algorithms for the Solution of Optimal Control, Design, and Inverse Problems

PLACE:	Clark 314
EVENT:	CIS Seminar Series
DATE:	April 27, 2006
TIME:	1:00 - 2:00

Abstract

Large scale optimization of systems governed by partial differential equations (PDEs) is a frontier problem in scientific computation. In practice, one is rarely content with performing a simulation of a physical or engineered system; sensitivity analysis, parameter estimation, and optimization are required for a complete analysis and to reflect design goals. Instead of traditional trial-and-error approaches, optimization techniques that are efficient for large-scale systems have been devised, and their use results in orders-of-magnitude savings over traditional methods.
In my talk I will describe a family of Multigrid-Newton-Krylov methods that enable enable the efficient and scalable solution of PDE-constrained optimization problems. I will present an anthology of examples in which such methods have been successfully applied: control of viscous incompressible flows, shape optimization of bodies immersed in Stokesian flows, source inversion in convective-diffusive systems, and parameter estimation in acoustic wave propagation.

Brief Biography

George Biros is an assistant professor in Mechanical Engineering and Applied Mechanics, and Computer and Information Science at the University of Pennsylvania. He received his BS in Mechanical Engineering from Aristotle University Greece (1995), his MS in Biomedical Engineering from Carnegie Mellon (1996), and his PhD in Computational Science and Engineering also from Carnegie Mellon (2000). He joined Penn in 2003 after serving as a postdoctoral associate at the Courant Institute of Mathematical Sciences at New York University. He is affiliated with the Computer Science Research Institute (CSRI) at Sandia National Laboratories.
Biros has research interests in Computational Science and Engineering. In particular, he works on computational mechanics, parallel algorithms for scientific computing, optimization algorithms, numerical methods for integral and differential equations. Applications include biological systems, fluid and solid mechanics systems, reaction systems, and electromagnetics. He has worked on PDE-constrained optimization algorithms for boundary/ distributed control and shape optimization for incompressible flows, and inverse problems for convection-diffusion, reaction diffusion, and acoustic equations; he has also worked on integral equations and parallel fast multipole algorithms for problems with dynamic interfaces.