About
I am a postdoctoral researcher at MIT CSAIL in Regina Barzilay's lab. I received my PhD in Computer and Information Science from the University of Pennsylvania in 2025, where I was advised by Jacob R. Gardner and supported by the NSF Graduate Research Fellowship.
My research focuses on probabilistic machine learning, Bayesian optimization, and generative modeling, with applications to scientific design problems. I have worked on optimizing antibiotics, antibodies, RNA sequences, and superconducting materials. My work on antimicrobial peptides achieved the first in vivo experimental validation of generative Bayesian optimization.
Selected Publications
A Generative Artificial Intelligence Approach for Antibiotic Optimization
Nature Biotechnology 2025 (Under Review) · paper
A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Design
NeurIPS 2025 · paper
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
NeurIPS 2025 · paper
Generative Modeling for RNA Splicing Predictions and Design
eLife 2025 · paper
Learned Offline Query Planning via Bayesian Optimization
SIGMOD 2025 · paper
Approximation-Aware Bayesian Optimization
NeurIPS 2024 Spotlight · paper
Joint Composite Latent Space Bayesian Optimization
ICML 2024 · paper
Discovering Many Diverse Solutions with Bayesian Optimization
AISTATS 2023 Notable Paper · paper · BoTorch tutorial
Local Latent Space Bayesian Optimization over Structured Inputs
NeurIPS 2022 · paper
See full list on Google Scholar
Awards & Invited Talks
- Invited Plenary Speaker, French Research Network on Uncertainty Quantification (RT-UQ) annual meeting – 2026
- Invited Speaker, Meta Adaptive Experimentation Workshop – 2025, 2024
- Invited Speaker, IMSI Workshop on Kernel Methods in Uncertainty Quantification and Experimental Design – 2025
- Invited Guest Lecturer, Columbia University PhD-level course on Bayesian optimization – 2024
- Invited Speaker, SIAM Conference on Uncertainty Quantification (SIAM UQ24) – 2024
- Invited Speaker, SIAM Conference on Computational Science and Engineering (SIAM CSE23) – 2023
- Notable Paper Award & Oral Presentation, Artificial Intelligence and Statistics conference (AISTATS) – 2023
- Fellowship Award, National Science Foundation Graduate Research Fellowship Program (NSF GRFP) – 2023
Organizing
- Co-organizer, Virtual Seminar Series on Bayesian Decision-making and Uncertainty – 2025
- Co-organizer, SIAM CSE Minisymposium on Uncertainty Quantification in Scientific Machine Learning – 2025
- Co-organizer, NeurIPS Workshop on Bayesian Decision-making and Uncertainty – 2024
Industry Experience
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BigHat Biosciences, ML Intern – Summer 2024
Developed structure prediction methods for antibody therapeutic design
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Meta, Central Applied Science Team, Research Intern – Summer 2023
Developed Bayesian optimization methods; first-author ICML 2024 paper
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NASA Jet Propulsion Laboratory, Research Intern – Summer 2020
Applied ML to ionospheric data; co-authored ESS 2021 paper