Pencina Named Chief Data Scientist
Michael Pencina, PhD, vice dean for data science, professor of biostatistics and bioinformatics at Duke University School of Medicine, and director of Duke AI Health, has been named Duke Health's first chief data scientist.
Executive Vice President for Health Affairs and Dean Mary E. Klotman, MD, and Duke University Health System Chief Executive Officer Craig Albanese, MD, MBA, announced Pencina’s appointment.
“In the current era of rapid expansion of AI and data science, we created this new role in recognition of the need for a well-articulated strategy for Duke Health that spans and connects both our academic and our clinical missions,” Klotman and Albanese said in their announcement. “Dr. Pencina will facilitate a strategic planning process to best align our priorities and resources and to build upon Duke's national leadership in trustworthy AI.”
Pencina will also partner with key leaders in Duke University School of Medicine and Duke University Health System to leverage and expand the opportunities afforded by the recently announced partnerships with Microsoft and nference.
As chief data scientist, Pencina will report to Klotman, DUHS Chief Digital Officer Jeffrey Ferranti, MD, and DUHS Chief Medical Officer Richard Shannon, MD. In addition, he will work in close partnership and alignment with the Department of Biostatistics and Bioinformatics and the Department of Population Health Sciences.
Pencina is uniquely qualified to bridge data science, health care, and AI. As vice dean for data science in the School of Medicine, he is responsible for developing and implementing quantitative science strategies as they pertain to the education and training and laboratory, clinical science, and data science missions of the School of Medicine. Previously, he served as director of biostatistics at the Duke Clinical Research Institute.
Pencina will continue spearheading Duke’s role as founding partner for the Coalition for Health AI, whose mission is to increase trustworthiness of AI by developing guidelines to drive high-quality health care through adoption of credible, fair, and transparent health AI systems. He is an internationally recognized authority in evaluation of artificial intelligence tools and algorithms for health expert panels, and guideline groups frequently rely on his work to advance best practices for application of algorithms in clinical medicine.