Rong Xu

Rong Xu is a Professor of Biomedical Informatics at Case Western Reserve University School of Medicine, where she also serves as Director of the Center for AI in Drug Discovery. She is a member of the Cancer Genomics and Epigenomics Program at the Case Comprehensive Cancer Center.

Dr. Xu's research focuses on developing innovative computational approaches including artificial intelligence, natural language processing, data mining, machine learning, and knowledge representation to advance biomedical discovery. Her work spans both computer science and biomedical science domains.

Her computer science research interests include Artificial Intelligence, Natural Language Processing, Machine Learning, Deep Learning, Systems Biology, Data Mining, Graph Theory, and Ontology. Her biomedical science interests encompass Drug Discovery, Drug Repositioning, Disease Gene Discovery, Gene-Environment Interactions, Human Gut Microbiome, Drug Target Discovery, Drug Toxicity Prediction, Cancer Drug Toxicity, Drug Addiction, and Neuroscience Informatics.

Dr. Xu's recent publications demonstrate a strong focus on applying AI and computational methods to drug discovery, particularly for neurological conditions, diabetes-related complications, and substance use disorders. Her work prominently examines the effects of GLP-1 receptor agonists like semaglutide on various health outcomes, including Alzheimer's disease, opioid use disorder, and cancer.

• Fellow of American College of Medical Informatics (FACMI) 2020
• American College of Medical Informatics Research Scholar 2016
• American Cancer Society New Investigator Award 2015
• American Medical Informatics Association AACR INNOVATOR Award 2015
• Landon Foundation Director's Innovator Award 2014
• National Institutes of Health Siebel Scholar 2004

Dr. Xu directs the Center for AI in Drug Discovery and has received significant grant funding for her research, including a $1.4 million grant from NIDA for developing AI technologies to identify potential medications for cocaine use disorder. Her work bridges computational science with clinical applications, focusing on translating AI discoveries into practical healthcare solutions.