Sharon E. Davis, PhD, MS

Research Assistant Professor
Department of Biomedical Informatics
2525 West End Ave
Suite 1400

Sharon E. Davis, PhD, is a Research Assistant Professor of Biomedical Informatics. She is a biomedical informatician with formal statistical training, who focuses on the development and maintenance of predictive models to support practical, implementable clinical prediction tools. Dr. Davis received an A.B. in Environmental Sciences and Policy from Duke University, a Masters in Statistics from North Carolina State University, and a PhD in Biomedical Informatics from Vanderbilt University. Her career is guided by a commitment to leveraging health and data sciences to develop tools that empower individuals, promote healthy communities, and reduce health disparities.

For over a decade, Dr. Davis served as a statistician and environmental scientist at Duke University and the University of Michigan. Her research emphasized the use of spatial analysis to address questions of maternal and child public health, as well as environmental justice. Key projects explored associations between air pollution, the built environment, psychosocial health, and pregnancy outcomes. This research led to practical solutions for community partners, including tools to support targeted community lead screening and data-driven community advocacy.

Since joining the Department of Biomedical Informatics, Dr. Davis’ research has emphasized methods development in support of predictive analytics, data simulation, and machine learning. Recognizing that the promise of prediction modeling and artificial intelligence to improve healthcare delivery requires accurate models that can sustain performance over time, Dr. Davis has developed a suite of generalizable and customizable methods supporting data-driven model updating for both regression and machine learning. These methods lay the groundwork for the design of automated model surveillance systems which will promote long-term performance and utility of prediction models underlying a variety of informatics applications for decision support and population management. This work was recognized by the AMIA community with the prestigious Martin Epstein award for the top student paper 2019 and with the honorable mention 2nd place Doctoral Dissertation Award in 2020. Extensions and applications of these methods remain an ongoing area of Dr. Davis’ research portfolio.

Within the Center for Improving the Public’s Health through Informatics, Dr. Davis’ research aims to develop and evaluate methods supporting the implementation of advanced and evolving predictive analytics in clinically useful interventions. With a continued focus on methods development and evaluation, she is involved in a variety of research projects exploring the practical challenges of applied predictive analytics within healthcare. In addition to research, Dr. Davis contributes to DBMI’s education mission as an instructor of both scientific communication and machine learning.