Zhuoran Qiao
Founding Scientist at Chai Discovery
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolZhuoran Qiao is a founding scientist and chemical physicist in San Francisco who applies physics-informed AI to chemistry, structural biology, and drug discovery, with nine years of experience spanning academia and industry. He has translated original research into core technology platforms for biotech startups, most recently building atomistic foundation models at Chai Discovery and leading development of NeuralPLexer iterations and Enchant at Iambic Therapeutics. His PhD-level background in theoretical chemistry and geometric learning from Caltech is complemented by hands-on molecular simulation and kinetics work from Peking University and Harvard. An active open-source contributor, he has improved critical protein parsing logic in the widely used ProDy library, reflecting attention to low-level data integrity that enables higher-level AI models. Colleagues rely on him to bridge rigorous physical modeling with scalable ML engineering to push translational science toward real-world drug discovery.
9 years of coding experience
8 years of employment as a software developer
北京理工大学附属中学California Institute of TechnologyBachelor of Science - BS Chemistry, Bachelor of Science - BS Chemistry at Peking University
English, Chinese, Japanese
Github Skills (7)
bioinformatics10
python10
dynamics9
file-access9
fileio9
file-processing9
file-handling9
Programming languages (5)
Github contributions (5)
prody/ProDy
Apr 2022 - Apr 2022
A Python Package for Protein Dynamics Analysis
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 1 PR, 5 comments in 2 days
Contributions summary:Zhuoran primarily focused on fixing and improving the bond matching algorithm within the `prody` library. Their work involved modifying the `pdbfile.py` to correct how bonds are parsed from CONECT records. Additionally, the user addressed issues with residue numbering and the handling of atom serial numbers, ensuring correct data processing. Their changes contribute to the accurate parsing of PDB files for protein structure analysis.
python-packageproteinpythondynamics
Utenaq/Water-Graphene-Binary
Jun 2017 - Oct 2020
Contributions:67 commits, 46 pushes, 3 branches in 3 years 5 months
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