Data Science Core

The Data Science Core provides a basis for data science discovery and engineering of translational biomedical informatics applications. Aims are to form and fund teams to address new health data science questions through an incubator program; develop new data science methods and informatics applications, and implement and disseminate data science tools.

Within the School of Medicine and across the entire University and its Health System, Duke is rich with intellectual, data and technological resources to further biomedical discovery. The Vice Dean for Data Science & Information Technology plays an essential role as a connector, conductor, and collaborator to ensure that key elements – IT, data, analysis, education, and partnerships – are aligned, designed and deployed in intentional, efficient, and sustainable ways to advance the School’s mission of teaching and research.

Leadership

Michael Pencina, PhD
Vice Dean of Data Science and Information Technology,
Director of AI Health

Shelley Rusincovitch, MMCi
Associate Director of Informatics, AI Health

Informatics Core

The Informatics Core is focused on innovative approaches that accelerate and transform scientific discoveries through data and applications that fuel translational research, data science and precision health; expand capacity for conducting collaborative network research and sharing network best practices; and provide access to opportunities for informatics training and professional development.

Core Aims

  • Provide data and applications that fuel translational research, data science, and precision health

  • Expand collaborative network research and sharing best practices

  • Build the biomedical informatics workforce at Duke

Leadership

Warren Kibbe, PhD
Professor in Biostatistics and Bioinformatics,
Chief for Translational Biomedical Informatics,
Chief Data Officer, Duke Cancer Institute

W. Ed Hammond, PhD
Professor of Community and Family Medicine,
Professor in Biostatistics and Bioinformatics

Benjamin A. Goldstein, PhD
Associate Professor in Biostatistics and Bioinformatics

To explore data science and information technology resources and support at the School of Medicine and beyond, visit: