Dr. Juan C. Meza
Dr. Meza has degrees in electrical engineering (B.S. 1978 and Masters 1979, Rice University) and mathematical sciences (Masters, Ph.D., 1986, Rice University). He is currently the Department Head of High Performance Computing Research at Lawrence Berkeley National Laboratory. This department focuses on research in scientific data management, visualization, numerical algorithms, and computational sciences and engineering. Prior to joining LBNL, Meza was a Distinguished Member of the Technical Staff at Sandia National Labs. Dr. Meza has served on numerous committees including the DOE Advanced Scientific Computing Advisory Committee, SIAM Board of Trustees, IMA Board of Governors, and MSRI Human Resources Advisory Committee. His current research interests include nonlinear optimization with an emphasis on parallel methods for simulation-based optimization. He has also worked on various scientific and engineering applications including methods for electronic structure calculations for nanoscience applications, mixed integer nonlinear programming methods for detecting vulnerabilities in electric power grids, optimization methods for molecular conformation problems, optimal design of chemical vapor deposition furnaces, semiconductor device modeling.
The Role of Mathematics in Amplifying Science Research
Computer modeling and simulation of physical processes has taken on an increasingly larger role in scientific research. In fact, computational science has become what some people term the "third pillar" of science along with theory and experimentation. This increased role is due partly to the tremendous growth in computational power. More importantly, however, the increased role is a direct result of a better understanding of the underlying mathematics and the development of improved algorithms. Examples from wide-ranging fields such as nanoscience, biology, climate modeling and astrophysics point not only to the role that mathematics plays in modeling physical processes but also in predicting new phenomena. In this talk, I will discuss several areas where mathematics has had a profound impact on science, and the role that mathematics has played in "amplifying" the research.
Level of the audience: general audience
Surface Structure Determination of Nanostructures Using a Mesh Adaptive Optimization Method
Many properties of nanostructures depend on the atomic configuration at the surface. One common technique used for determining this surface structure is based on the low energy electron diffraction (LEED) method, which uses a sophisticated physics model to compare experimental results with spectra computed via a computer simulation. While this approach is highly effective, the computational cost of the simulations can be prohibitive for large systems. In this work, we propose the use of generalized pattern search methods, which can handle both discrete and continuous variables and allows the simultaneous optimization of the atomic coordinates as well as the chemical identity. We will present some numerical results based on a mesh adaptive direct search (MADS) algorithm developed by Abramson and Dennis.
Level of audience: 2nd-year graduate students
The Unwritten Rules of Interviewing
There are many ways to make a good impression when interviewing for a job and infinitely many more ways to make a bad impression. Did you ever wonder why after an apparently good interview, you were never called back or offered that job you really wanted? Based on my experiences having watched many bright young students come through and self-destruct during the interview, this talk is for anyone that is interested in learning about what goes on behind the scenes before, during, and after the interview. I will highlight the talk with real-life experiences and explain what went wrong, why it went wrong, how you can avoid these mistakes and how you can make the best impression.
Level of audience: All students