Yong Chen, PhD, is a Professor of Biostatistics and Founding Director of the Center for Health AI and Synthesis of Evidence (CHASE) at the University of Pennsylvania, where he leads research in clinical evidence generation and synthesis using real-world data. He also directs the Penn Computing, Inference, and Learning (PennCIL) Lab, focusing on developing methods for integrating clinical data.
Dr. Chen serves as a Statistical Editor for the Annals of Internal Medicine, a Statistical Consultant for New England Journal of Medicine-AI, and an Associate Editor for both the Journal of the American Statistical Association – Applications and Case Studies (JASA-ACS) and The Annals of Applied Statistics (AoAS).
Dr. Chen’s research has been continuously supported by the National Institutes of Health (NIH), Agency for Healthcare Research and Quality (AHRQ), and Patient-Centered Outcomes Research Institute (PCORI). He is currently the principal investigator on more than 10 research awards from NIH and PCORI. In particular, he is the contact principal investigator for a U01 award funded by the National Center for Advancing Translational Sciences (NCATS) on developing evidence synthesis and data integration methods using electronic health records from multiple Clinical and Translational Science Awards (CTSA) hubs to create predictive models of rare multi-system diseases. These include granulomatosis with polyangiitis (GPA), a type of vasculitis with a prevalence of approximately 74 per million; psoriatic arthritis (PsA), approximately 2,500 per million; eosinophilic granulomatosis with polyangiitis (EGPA); giant cell arteritis (GCA); and ankylosing spondylitis.
Dr. Chen has authored more than 200 peer-reviewed papers in statistics and medical informatics. His work focuses on evidence synthesis, machine learning and artificial intelligence, and clinical evidence generation. He is an elected Fellow of the American Statistical Association and the American College of Medical Informatics, with joint appointments in Applied Mathematics and at the Penn Institute for Biomedical Informatics.