New Alvarez Fellow Joins CRD
Yu-Hang Tang seeks to improve molecular dynamics simulations.
October 27, 2017
Cleighton Roberts firstname.lastname@example.org
Yu-Hang “Maxin” Tang, the most recent recipient of the Alvarez Postdoctoral Fellowship, will be working to use active learning algorithms to accelerate computationally expensive scientific computations such as ab initio molecular dynamics. His work is applicable to many different kinds of systems, such as enzymes and catalysts, by improving existing molecular dynamics simulations by including the ability to model chemical reactions in addition to other physical interactions.
He will be working with the Lawrence Berkeley National Laboratory’s Computational Chemistry, Materials and Climate Group, which is a part of the Computational Research Division. He felt compelled to get a fellowship at the Berkeley Lab because the research areas are relevant to what Tang is doing while being “one of the best research institutions that brings fundamental science into solving real-world challenges.”
The Berkeley Lab Computing Sciences Alvarez Postdoctoral Fellowship program allows graduates to work on the most important research challenges in applied math, computer science, and computational science. The Alvarez Fellowship was founded in 2002 and was named after Luis W. Alvarez, a Nobel laureate in physics who was one of the first scientists to propose using computers to analyze scientific data.
Tang has a history with computational science. While getting his Ph.D. he worked on developing methods for several different simulations, including large-scale computations which were capable of simulating the interactions of one million red blood cells.
He first became interested in computational science while getting his bachelor’s degrees in polymer science from Zhejiang University in his native China. In 2011 he came to the United States and attended Brown University where he got his Ph.D. in applied mathematics. He enjoys his research because “it connects the practical world with theoretical development.”
In his free time Tang enjoys spending time outdoors doing activities such as hiking and photography. While living on the East Coast he also picked up skiing.
Editor's note: This article was written by Albany High School intern Cleighton Roberts.
About Computing Sciences at Berkeley Lab
The Lawrence Berkeley National Laboratory (Berkeley Lab) Computing Sciences organization provides the computing and networking resources and expertise critical to advancing the Department of Energy's research missions: developing new energy sources, improving energy efficiency, developing new materials and increasing our understanding of ourselves, our world and our universe.
ESnet, the Energy Sciences Network, provides the high-bandwidth, reliable connections that link scientists at 40 DOE research sites to each other and to experimental facilities and supercomputing centers around the country. The National Energy Research Scientific Computing Center (NERSC) powers the discoveries of 6,000 scientists at national laboratories and universities, including those at Berkeley Lab's Computational Research Division (CRD). CRD conducts research and development in mathematical modeling and simulation, algorithm design, data storage, management and analysis, computer system architecture and high-performance software implementation. NERSC and ESnet are DOE Office of Science User Facilities.
Lawrence Berkeley National Laboratory addresses the world's most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab's scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the DOE’s Office of Science.
DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.