I am an MIT PhD student in Debora Marks lab (Harvard). I am interested in deep generative models of proteins, especially modeling viral and antibody sequences and structures. My research develops models to learn viral antibody escape by combining fitness models with biophysical and structural information. These models can be used to identify high escape variants and to design and test future-proof vaccines.
Interests
- Machine learning for biology
- Computational vaccine design
- Viral evolution
- Protein engineering
Education
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MS in Electrical Engineering and Computer Science, 2023
Massachusetts Institute of Technology
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BS in Computer Science, 2020
Stanford University
Publications
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(2024).
Future-proof vaccine design with a generative model of antibody cross-reactivity.
ICLR Workshop on Generative and Experimental Perspectives for Biomolecular Design.
(2024).
Protein design for evaluating vaccines against future viral variation.
BioRxiv.
(2023).
Learning from prepandemic data to forecast viral escape.
Nature.
(2023).
Removing bias in sequence models of protein fitness.
BioRxiv.
(2023).
Reprogramming Cancer into Antigen-Presenting Cells as a Novel Immunotherapy.
Cancer Discovery.