Dr. Sam Pyne

Dr. Sam Pyne's areas of research interest include computational statistics, AI/ML, health and environmental data science strategies. He received his Ph.D. in Computational Biology from the State University of New York at Stony Brook and postdoctoral training at the Broad Institute of MIT and Harvard University.

Dr. Pyne has extensive experience in advisory, strategic, and supervisory roles. He has created and led new departments, labs, and companies as well as led national level initiatives and task forces in AI, Big Data, Public Health, etc. His community leadership projects received support from prominent agencies such as the NIH Fogarty and the Medical Research Council, UK. He served as a co-Chair of IEEE Big Data for multiple years.

Dr. Pyne is known for several path-breaking contributions in health data science, statistics and bioinformatics. He has described novel strategies for objective evaluation of data assets and data benchmarking. His research led to new advances including modeling of population heterogeneity, spatial complexity, inference of dynamic phenomena using real and synthetic data fusion, systematic integration of high-dimensional data, multivariate skew mixture models and automated modeling of complex immuno-phenotypes.

Dr. Pyne held different positions at premier institutions such as MIT, University of California Santa Barbara, University of Pittsburgh, Harvard Medical School, Indian Statistical Institute, Indian Institute of Public Health, CR Rao AIMSCS and National Institute of Medical Statistics, New Delhi. He has served in many capacities including the PC Mahalanobis Chair, Full Professor and Head, Research Scientist, Scientific Director, Ramalingaswami Fellow, Senior Research Fellow, and Visiting Professor.

In recent years, Dr. Pyne was a Senior Research Fellow at NIH and a National Service DATA Scholar developing a new ecosystem for interoperability and reuse of data. He has published a 2-volume Handbook of Statistics on Disease Modeling and Public Health (Elsevier) and texts on Big Data Analytics (Springer) and Big Data Benchmarking (LNCS, Springer).

Currently, Dr. Pyne leads an international team of data scientists and disease modelers as the Chief Strategist at the Health Analytics Network. His present research focuses on aging and models of degenerative processes, circular functional modeling of circadian data, and applications of Generative AI and Data Fusion. As a former member of the HHS AI Task Force, he is particularly interested in evaluating and promoting best practices for data access, sharing and reuse.