Tao Cheng
Research Scientist In JCAP at THE JOINT CENTER FOR ARTIFICIAL PHOTOSYNTHESIS
Pasadena, California, United States
Summary
👤
Senior🎓
Top SchoolTao Cheng is a research scientist at the Joint Center for Artificial Photosynthesis with 13 years of experience applying statistical thermodynamics, molecular dynamics, and Monte Carlo methods to probe microscopic fluid structure, interfaces, and condensed-phase reactions. He has deep expertise in force field development, custom simulation algorithm implementation, and high-performance scientific coding—primarily in C, with substantial C++ and Fortran work—and has written tens of thousands of lines of simulation code. Tao’s background spans academia and national labs, including a Caltech postdoc and a PhD from Shanghai Jiao Tong University, where he developed hybrid MD/MC techniques for complex liquid systems. Based in Pasadena, he combines quantum chemistry tools (Gaussian, Turbomole) with MD packages (LAMMPS, GROMACS, AMBER) and practical cluster/network management, making him adept at moving methods from prototype to production-scale simulation. An underappreciated strength is his history of modifying core simulation engines to embed novel algorithms, enabling multi-scale predictions of physical and chemical properties.
13 years of coding experience
Doctor of Philosophy (Ph.D.), Chemistry, Doctor of Philosophy (Ph.D.), Chemistry at Shanghai Jiao Tong University
Chinese, English
Github Skills (6)
dft4
materials-informatics4
theory3
machine-learning3
data-science2
density-functional-theory2
Programming languages (3)
Github contributions (5)
ensemble-learning/simpy
Jan 2013 - Dec 2022
Contributions:349 commits, 249 pushes in 10 years 1 month
ensemble-learning/ensemble-learning.github.io
Oct 2016 - Feb 2023
Contributions:705 commits, 1388 pushes, 1 branch in 6 years 4 months
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