Dr. Kexin Huang
AI Bio-Medicine Researcher
Postdoctoral Research Fellow at Stanford University and Harvard Medical School. Creator of Therapeutics Data Commons (TDC) and TxGNN, the landmark foundation model for clinician-centered drug repurposing published in Nature Medicine, pioneering graph AI in biomedicine.
Areas of focus
Professional niches
Proof of Work
A Foundation Model for Clinician-Centered Drug Repurposing with TxGNN
First author of the Nature Medicine 2024 paper introducing TxGNN, a geometric foundation model trained on a medical knowledge graph of 17,080 diseases to identify drug repurposing opportunities for rare diseases with clinician-interpretable rationales.
Predictions require in vitro wet-lab assay validation and clinical trials before therapeutic efficacy can be established.
Context: Graph Neural Networks, 17k disease knowledge graph, clinician explanatory subgraphs.
View missionTherapeutics Data Commons: Machine Learning Benchmarks for Drug Discovery
Co-founded and engineered Therapeutics Data Commons (TDC), the de-facto open-source Python library standardizing 66 therapeutic machine learning tasks across small molecules, antibodies, target proteins, and clinical outcomes.
Public biological datasets often carry historical batch effects that require careful domain covariate shift evaluation.
Context: PyTorch Geometric, RDKit integration, 66 benchmark tasks across 22 problem formulations.
View mission