I'm currently a final-year PhD student at the University of California, Berkeley, advised by
My research contributes to the machine learning foundation for
the design, engineering, and interpretation of proteins.
This includes new methods for structure-based protein design and
for ranking sequence variants in protein engineering campaigns.
Most recently, I have been focusing on immune repertoires. I
believe that machine learning advances in structural biology and
in protein sequence modeling will lead to progress in immunology,
such as a better understanding of autoimmunity and immunogenicity.
Some of my recent work was done during an internship with
Lerer and the Protein team (led by
Tom Sercu) at Facebook AI Research.
I was also fortunate to explore the topics of protein design and
immunology from a commercial perspective as a Bio-IT Fellow at
Earlier work experience as machine learning engineer at Google
Health helped shape my interests in human health.
Deep gratitude also goes towards
Chris Umans and
for their kind and inspiring mentorship during
my undergraduate years at Caltech.
(Last updated: January 2023)
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