Education

Ph.D in Biochemistry and Molecular Biology, Caltech, 2024/2025
B.S. in Computer Science - Biocomputation, Stanford University, 2019
- Visiting student at University of Oxford through Stanford Bing Overseas Studies Program (09/2018 - 03/2019)

Selected professional experience

Research Associate - MLCV@SLAC (09/2024 - present)
- Develop and implement machine learning algorithms for macromolecular crystallography, and translate research outcomes into operations at LCLS. Slides (2025 ACA Invited Talk)
- Support user experiments by assisting their data analysis for real-time feedback and reprocessing.
- Mentor students on research projects.
Doctoral research - Caltech (09/2019 - 08/2024)
- Developed machine learning-based methods for small molecule electron diffraction data processing. Preprint
- Developed multi-scale free energy calculation methods for probing PROTAC-mediated protein-protein interactions. Publication
- Contributed to montage cryo-electron tomography method development on data collectionby simulating radiation damage patterns. Publication
Intern in Chemistry, Modeling, & Informatics - Merck (06/2018 - 09/2018)
- Analyzed in-house computational models to predict small moleculedrug properties. Publication
Undergraduate research assistant - Stanford University (02/2017 - 06/2018)
- Contributed to a graph-based model for predicting protein-ligand binding and other ligand properties. Publication

Peer reviewer, Proceedings of the National Academy of Sciences (PNAS)
Peer reviewer, Journal of Chemical Information and Modeling (JCIM)
Peer reviewer, FEBS Open Bio
Peer reviewer, Neural Information Processing Systems (NeurIPS) ML4PS workshop
Poster award judge for the Journal on Structural Dynamics at 2025 ACA Meeting
Lead organizer of the workshop “Building a General Inference Engine for Molecular Structures and Ensembles” at the 2025 LCLS/SSRL Users’ Meeting
IUCr Early Career Board (2025-2028) for Acta Crystallographic D and Acta Crystallographic F