Chenxing Luo
Hess Fellow at Princeton University
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolChenxing Luo is a Ph.D. candidate-turned-Hess Fellow specializing in atomistic simulation and first-principles studies of solids under extreme pressure and temperature. With nine years of experience across Columbia, Lamont-Doherty, and Princeton environments, Chenxing blends deep expertise in elasticity, thermoelasticity, and hydrogen-bond physics with practical computational geochemistry and geophysics. He builds bespoke software and workflows to accelerate research, bridging physics-first theory with reproducible tooling for complex simulations. He has taught applied linear algebra and materials behavior, reflecting a talent for translating theory into usable methods. Based in New York and active in the MineralsCloud research community, he brings both rigorous academic training and hands-on engineering to problems at the physics–computing interface.
9 years of coding experience
9 years of employment as a software developer
The High School Affiliated to Renmin University of ChinaBachelor of Science - BS, Materials Physics, Bachelor of Science - BS, Materials Physics at Nanjing UniversityDoctor of Philosophy - PhD, Materials Science and Engineering, Doctor of Philosophy - PhD, Materials Science and Engineering at Columbia University in the City of New YorkBeijing Bayi Middle School.
English, Chinese
Stackoverflow
546reputation
39kreached
28answers
0questions
Github Skills (200)
colorize10
instagram10
python10
energy10
ase10
computational-chemistry10
telegram10
deep-learning10
visual-studio10
phonetics10
cpp10
spotify10
rss10
twitter10
rss-reader10
Programming languages (13)
Github contributions (5)
chazeon/dpgen-snakemake
Jul 2021 - Jul 2022
Contributions:44 commits, 39 pushes, 2 branches in 1 year
chazeon/deepmd-kit
Sep 2021 - May 2024
A deep learning package for many-body potential energy representation and molecular dynamics
Contributions:32 pushes, 6 branches in 2 years 8 months
representationmolecular-dynamicsdeep-learningbodymolecular
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