Yepeng Huang

Medea, an AI agent, performs therapeutic reasoning across biological contexts by preserving context, verifying steps, and reconciling evidence, outperforming existing models in multiple domains.

This paper introduces a multimodal foundation model for predicting protein phenotypes using sequence, structure, and natural language, showing competitive performance and novel insights into disease-related proteins.

This paper introduces a geometric deep learning model for context-aware protein representations, improving therapeutic target nomination in immune-related diseases.