I am a Ph.D. student in Computational Biology and Bioinformatics at Yale University, advised by Dr. Qingyu Chen in the Department of Biomedical Informatics & Data Science. I also work with Dr. Carlos Oliver at Vanderbilt's Center for AI in Protein Dynamics.
My research builds AI systems for scientific discovery: agents for data-driven discovery, protein and RNA language models, generative models for biomolecular design, and rigorous evaluation of AI agents on real scientific tasks.
Before Yale, I earned an M.S. in Computer Science from Vanderbilt University, where I worked with Dr. Tyler Derr and Dr. Jens Meiler on data-centric machine learning for drug discovery, and a B.S. in Statistics and Data Science from UC Santa Barbara, where I worked with Dr. Eleanor Caves on computer vision for biological image analysis.
Research Interests
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AI agents for scientific discovery
Agents for data-driven discovery, and rigorous evaluation of AI agents on real scientific tasks.
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Protein & RNA language models
Learning representations of biomolecules from sequence and structure.
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Biomolecular design
Generative models, including diffusion language models, for designing and optimizing biomolecules.
News
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BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction accepted at NeurIPS 2026.
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Gave a contributed talk on Benchmarking AI Agents for Addressing Scientific Challenges Across Scales at the AI Scientist Summer Workshop (Microsoft Research New England).
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Scaffold-Aware Generative Augmentation and Reranking for Enhanced Virtual Screening accepted at SDM 2026.
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Released Benchmarking AI Agents for Addressing Scientific Challenges Across Scales (co-first author) and AI Scientists in Health: Trustworthy Agentic AI for Scientific Inquiry.
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Started my Ph.D. in Computational Biology & Bioinformatics at Yale University.
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Presented WelQrate: Defining the Gold Standard in Small Molecule Drug Discovery Benchmarking at the NeurIPS 2024 Datasets and Benchmarks Track.
Selected Publications
All publicationsAI Scientists in Health: Trustworthy Agentic AI for Scientific Inquiry
Submitted to Nature Biomedical Engineering, 2026
Talks
- Benchmarking AI Agents for Addressing Scientific Challenges Across Scales