Jason H. Moore

Dr. Moore is an Adjunct Professor of Biostatistics with research interests in biomedical data science and statistical genetics. He focuses on the development, evaluation, and application of artificial intelligence and machine learning methods for developing predictive models of clinical outcomes including risk of common diseases such as cancer, cardiovascular disease, and neuropsychiatric diseases such as Alzheimer's. His current research includes the development of automated machine learning methods (AutoML) for the analysis of big data from genetic and genomic studies and the electronic health record. His Tree-Based Pipeline Optimization Tool (TPOT) was one of the first and most widely used AutoML methods.

Dr. Moore serves as Chair of the Department of Computational Biomedicine at Cedars-Sinai Medical Center. He is an elected Fellow of the American Statistical Association (ASA) and an elected Member of the International Statistics Institute (ISI). He is also an elected Fellow of the American College of Medical Informatics (ACMI), the International Association for Health Sciences Informatics (IAHSI), and the American Association for the Advancement of Science (AAAS). He is Editor-in-Chief of the open-access journal BioData Mining.


  • Ph.D., Human Genetics, University of Michigan
  • M.A., Applied Statistics, University of Michigan
  • M.S., Human Genetics, University of Michigan
  • B.S., Biological Sciences, Florida State University