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
Services
- 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