I am a FutureHouse AI-for-Science Independent Postdoctoral Fellow. I am co-advised by Sergey Ovchinnikov (MIT) and Aaron Schmidt (Ragon). I work on deep generative models of proteins, with a focus on modeling viral and immune protein sequences and structures.

I recently completed my PhD in Electrical Engineering and Computer Science at MIT (and a short postdoctoral stint) in Debora Marks lab at Harvard. My previous research focused on developing models to learn viral antibody escape from fitness models and 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
  • Viral-host interactions
  • Protein engineering
Education
  • PhD in Electrical Engineering and Computer Science, 2025

    Massachusetts Institute of Technology

  • MS in Electrical Engineering and Computer Science, 2023

    Massachusetts Institute of Technology

  • BS in Computer Science, 2020

    Stanford University

Publications

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(2025). Variant effect prediction with reliability estimation across priority viruses. BioRxiv.

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(2025). Forecasting H1N1 Influenza Pandemic and Seasonal Evolution. ICML Workshop on Generative AI for Biology.

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(2025). Computationally designed proteins mimic antibody immune evasion in viral evolution. Immunity.

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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.

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(2023). Learning from prepandemic data to forecast viral escape. Nature.

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