Meet the CSGF Fellows at Berkeley Lab
June 30, 2009
Five fellows from the Department of Energy's Computational Science Graduate Fellowship (CSGF) are honing their computational science skills at the Lawrence Berkeley National Laboratory (Berkeley Lab) this summer.
The five students will assist researchers in the Lab's Computational Research Division (CRD), Life Sciences Division, and Molecular Foundry, where they will contribute to groundbreaking research that will help engineers design better medical imaging tools, airplanes, and tailor treatments for cancer patients, among other things.
“The Berkeley Lab is fortunate to have an exceptionally bright group of CSGF research fellows this summer. The talented pool made my role of connecting fellows with LBNL hosts and projects really easy,” says Daniel Martin, coordinator for the CSGF fellowship program at the Berkeley Lab and a member of the Applied Numerical Algorithms Group.
As an alumnus of the program, Martin credits his fellowship experience with leading directly to his position at the Berkeley Lab, and says he feels honored to contribute to the success of a new generation of fellows as a program coordinator.
The CSGF program was developed in 1991 to meet the nation's need for science and technology professionals with advanced computer skills. Benefits of the program include a yearly stipend of $32,400, payment of all graduate school tuition and fees, and funds for computers and travel to conferences. DOE's Office of Advanced Scientific Computing Research (ASCR) and the National Nuclear Security Administration's Advanced Simulation and Computing (ASC) program jointly fund the program, while the Krell Insitute administers the benefits.
This summer's CSGF fellows at Berkeley Lab include:
Douglas Mason
 |
| Doug Mason |
“The human mind is the only limit to a computer's capabilities, and my ultimate goal is to push the performance limits for analyzing large data sets,” says Douglas Mason, a graduate student from Harvard University.
This summer, Mason will be learning about data portals as he assists Peter Nugent of CRD's Computational Cosmology Center with the Deep Sky Project – a public gateway to the National Energy Research Scientific Computing Center's astronomical archive, which contains more than 11 million cosmic images. The Deep Sky project's online tools and services will give researchers around the world an opportunity to instantly search, download and analyze this data.
Although Mason is new to CRD, he is not new to the Berkeley Lab. As part of the CSGF program, he also spent the last academic year working with Jeffery Neaton, a staff scientist in the Materials Sciences Division, to develop and understand theories of nanoscale materials. This knowledge will enable the development of ever-smaller electronic devices.
Originally from Akron, Ohio, Mason says he'll miss the world-class research at Berkeley Lab, the Triple Rock Brewery, and Northern California weather most when he returns to Boston this fall to complete his doctorate degree in Physics.
Britton Olson
 |
| Britton Olson |
“I was initially exposed to supercomputers as an undergraduate research assistant at the Lawrence Livermore National Laboratory, and remember being really excited to learn that computer algorithms could predict the effects of a wide-range of phenomenon, from supernovae detonations to shock waves on airplanes,” says Britton Olson, a graduate student at Stanford University.
This summer, Olson will be assisting CRD senior staff scientist Philip Colella develop algorithms that will make atmospheric models more accurate. He will primarily be focusing on the new high-order finite-volume methods for mapped multiblock grids, which is being developed at the Berkeley Lab.
Originally from Brentwood, Calif., Olson earned a Bachelor of Science degree in mechanical engineering from Brigham Young University. For his graduate work, he decided to couple a love for airplanes with his interest in engineering and physics to pursue a Ph.D. in aeronautical engineering.
“My decision to pursue an advanced degree in the sciences came to me by the fifth grade. The example of various mentors as well my affinity for taking things apart fueled this long-term goal,” says Olson.
In his spare time, Olson likes to build and fly radio controlled (RC) airplanes, play squash, volleyball and tennis. Otherwise he can be found spending time with his wife and newborn son, William.
Eric Liu
 |
| Eric Liu |
"I was drawn to applied math because it allowed me to use mathematics to solve practical problems, like designing effective helmets or more efficient airplanes. I develop the algorithms and let computers solve the problems," says Eric Liu, a graduate student at the Massachusetts Institute of Technology (MIT). This summer, Liu will also be assisting CRD's Colella to develop a method that will accurately simulate traveling shockwaves in air and water.
Originally from Cary, North Carolina, Liu earned a Bachelor of Science from MIT in Aerospace Engineering and Mathematics, and is now pursuing an advanced degree in Computational Fluid Mechanics. Liu's interest in math and science was sparked by his undergraduate academic and research advisor, David Darmofal, who is also his graduate thesis advisor.
This summer's trip to Berkeley will be the furthest that Liu has ever traveled for an extended period of time, but he is excited to explore a new city. In his spare time, he enjoys playing games with friends, cooking, and watching movies.
Ying Hu
 |
| Ying Hu |
"Computers are powerful tools for tackling a variety of difficult challenges. Often times, simulations are the most time and cost-effective means to provide experimental insights. With the supercomputing power, we can explore new models with larger scales and more degrees of complexity. This sounds very exciting, but there is a catch, namely, parallelization of the code, and this by no means is an easy task," says Ying Hu, a postdoctoral candidate from Rice University.
This summer, Hu will be assisting staff scientist James Schuck and facility director Jeff Neaton in the Berkeley Lab's Molecular Foundry, where he will work on a parallel finite-difference time-domain (FDTD) code that accurately simulates how light scatters upon interaction with a range plasmonic nanostructures. He notes that this research could advance the fundamental understanding of nanophotonics to overcome diffraction limit and also help researchers design new imaging contrast agents and novel instrumentations for cancer diagnosis.
Hu started developing electromagnetics computational codes in 2007 when he visited the University of Queensland in Australia on an NSF summer program. While at the Centre for Biophotonics and Laser Science in UQ, he studied Mie theory and developed an analytical program that calculates light scattering from concentric spherical nanoparticles. The code will serve as a validation tool for the parallel FDTD code he will be working on this summer.
Originally from the Hunan Province in China, Hu came to the United States in 2002 and attended the University of Houston in Texas. He earned a Bachelor of Science degree in electrical engineering in 2006, and is currently pursuing a doctorate in Bioengineering at Rice University in Texas. He looks forward to the cool summer weather in Berkeley and hopes to take advantage of it by spending his spare time hiking the beautiful mountains and valleys.
Eric Chi
 |
| Eric Chi |
"Like all cancers, breast cancer isn't one disease but many. Some kinds will respond to one treatment while others won't. It'd be great to have the most accurate information on a patient's cancer subtype before treatment starts. We can use computational algorithms to predict how an individual's genetic code may influence the patient's survival rate on different treatments,” says Eric Chi, MD/PhD student at Rice University and Baylor College of Medicine.
This summer, Chi will be working with computational scientist Paul Spellman of the Lab's Life Sciences Division to refine the classification of breast cancer according to criteria that include treatment sensitivity and patient survival based on genomic data. He will use statistical methods to find patterns in thousands of genomic measurements that have previously been collected, and examine their responses to different drugs.
Originally from Dallas, Texas, Eric earned a Bachelor of Science degree in physics from Rice University in 1999, a Master of Science in electrical engineering from the University of California, Berkeley in 2001, and is currently pursuing a doctorate in Statistics at Rice University and medical doctorate at Baylor College of Medicine.
He plans on maximizing Berkeley's cool summer weather by spending much of his spare time outside, hiking with his family.
For more information on the CSGF fellows, please visit: http://www2.krellinst.org/csgf/index.shtml.
