Precision Medicine Maria Mayorga

Associate Professor, Industrial and Systems Engineering

image of maria mayorga

Contact Information

Daniels Hall 376
Raleigh, NC

Maria E. Mayorga joined NC State in August 2013 as a Chancellor’s Faculty Excellence Program cluster hire in Precision Medicine. She is an associate professor in the Edward P. Fitts Department of Industrial and Systems Engineering and part of the Healthcare Systems Engineering group. Her goal is to address fundamental research barriers in moving from estimates of efficacy to estimates of effectiveness of interventions or policies by explicitly considering individual patient preferences, when the underlying patient population is heterogeneous. She is also interested in optimally allocating resources in emergency medical service systems. To achieve these goals, Mayorga creates analytical models of health systems that incorporate patient-level data. She uses techniques such as simulation, dynamic programming, applied probability, queuing theory and mathematical programming. Mayorga employs multiple sources of secondary data and a mixed methods approach to enable predictions of health outcomes at levels for which it is difficult to conduct studies in practice. This research is inherently interdisciplinary and is thus facilitated via collaborations with health services researchers such as epidemiologists, economists and medical doctors.

Mayorga received a bachelor of science in mechanical engineering from The George Washington University. She earned her master of science and Ph.D. in industrial engineering and operations research from the University of California, Berkeley. Previously, she was on the faculty at Clemson University in the Department of Industrial Engineering. She has authored more than 40 publications in archival journals and refereed proceedings. Her research has been supported by the National Institutes of Health and the National Science Foundation, among others. She received the distinguished NSF Faculty Early Career Development Award for her work to incorporate patient choice into predictive models of health outcomes.