Philip R.O. Payne, PhD, FACMI, FAMIA, FAIMBE

Janet and Bernard Becker Professor and Director, Institute for Informatics (I2)

Associate Dean for Health information and Data Science, School of Medicine

Chief Data Scientist, School of Medicine

Philip R.O. Payne, PhD, FACMI, FAMIA, FAIMBE, is the founding director of the Institute for Informatics (I2) at Washington University in St. Louis, where he also serves as the Janet and Bernard Becker Professor and Professor of Computer Science and Engineering. Previously, Dr. Payne was Professor and Chair of the Department of Biomedical Informatics at The Ohio State University.


Dr. Payne is an internationally recognized leader in the field of clinical research informatics (CRI) and translational bioinformatics (TBI). His research portfolio is actively supported by a combination of NCATS, NLM, and NCI grants and contracts, as well as a variety of awards from both nonprofit and philanthropic organizations.

Dr. Payne received his Ph.D. with distinction in Biomedical Informatics from Columbia University, where his research focused on the use of knowledge engineering and human-computer interaction design principles in order to improve the efficiency of multi-site clinical and translational research programs. Prior to pursuing his graduate training, Dr. Payne served in a number of technical and leadership roles at both the UCSD Shiley Eye Center and UCSD Moores Cancer Center.

Dr. Payne’s leadership in the clinical research informatics community has been recognized through his appointment to numerous national steering, scientific, editorial and advisory committees, including efforts associated with the American Medical Informatics Association (AMIA), AcademyHealth, the Association for Computing Machinery (ACM), the National Cancer Institute (NCI), the National Library of Medicine (NLM) and the CTSA consortium, as well as his engagement as a consultant to academic health centers throughout the United States and the Institute of Medicine.

Research Interests

  • Cognitive computing and machine learning based approaches to the discovery and analysis of bio-molecular and clinical phenotypes and the ensuing identification of precision diagnostic and therapeutic strategies in cancer and other clinical conditions
  • Interventional approaches to the use of electronic health records in order to address modifiable risk factors for disease and enable patient-centered decision making
  • The study of human factors and workflow issues surrounding the optimal use of healthcare information technology

Lab Members

  • Kelly Regan, PhD, The Ohio State University College of Medicine
  • Aditi Gupta, PhD, Instructor in Biostatistics, Washington University School of Medicine in St. Louis, Division of Biostatistics
  • Inez Oh, PhD, Staff Scientist, Washington University School of Medicine in St. Louis, Institute for Informatics
  • Lin Zhang, Statistical Data Analyst, Washington University School of Medicine in St. Louis, Institute for Informatics
  • Sayantan Kumar, PhD Student in Computer Science & Engineering, Washington University in St. Louis, McKelvey School of Engineering