Juan Meza's SIAM Visiting Lecturer Program Talks
High Performance Computing Research
Lawrence Berkeley National Laboratory
1 Cyclotron Road
MS 50B-4230
Berkeley, CA 94720
(510) 486-7684
email: JCMeza@lbl.gov
I am a member of SIAM's Visting Lecturer program
which offers speakers on various topics in applied mathematics
and computing for the use of university groups. SIAM distributes this
information to SIAM student chapters as well as posting it on the SIAM
web page to encourage institutions to invite speakers of their choice
to interact with students and faculty. By reaching students and
faculty we try to promote applied mathematics and computing. In
addition to the talks listed in my presentations page, the following
talks might be of special interest to students.
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
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 variable 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.
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. An html version of the talk can be found here