Fuhai Li

Fuhai Li, PhD, is an Associate Professor of Pediatrics at the Washington University School of Medicine. He holds dual affiliations with the Roy and Diana Vagelos Division and the Division of Biology & Biomedical Sciences (DBBS) in the areas of Biomedical Informatics, Cancer Biology, and Computational and Systems Biology. His research spans multiple institutions including the Institute of Clinical and Translational Sciences (ICTS), Institute for Informatics, Data Science and Biostatistics (I2DB), Center for Translational Bioinformatics (CTBI), and Siteman Cancer Center.

• Biomedical Informatics and Data Science
• Cancer Biology
• Computational and Systems Biology

Dr. Li specializes in integrating pharmacogenomics data through statistical and machine learning approaches. His work focuses on three key areas: 1) identifying driver genetics in diseases, 2) developing novel drug combinations to combat resistance with reduced toxicity, and 3) analyzing tumor-stroma interactions to understand microenvironment roles in disease progression. His research employs advanced techniques like multi-scale graph AI models, deep learning for disease prediction, and tools for multi-omics signaling network generation.

Recent publications demonstrate expertise in graph neural networks for multi-omic data analysis, deep learning applications in glaucoma prediction, and integrative computational approaches in cancer research. His work aligns with precision medicine and translational bioinformatics paradigms.

Dr. Li is actively involved in mentoring PhD and MSTP students, with over 4,000 citations to his research output spanning 2005-2025. He has published extensively in computational biomedicine, including editorials in Computational and Structural Biotechnology Journal and Cancers.

Key collaborations include the Roy and Diana Vagelos Division, ICTS, I2DB, and Siteman Cancer Center. His research tools like mosGraphGen demonstrate commitment to developing interpretable AI frameworks for biomedical discovery.