UNIVERSITY PARK, Pa. — Wenrui Hao, professor of mathematics in the Penn State Eberly College of Science and 2025-26 Huck Leadership Fellow, has been named the new director for the Center for Mathematical Biology in the Huck Institutes of the Life Sciences.
The Center for Mathematical Biology fosters the exchange of ideas and the development of research collaborations involving mathematical models and quantitative approaches to the life sciences. Hao will host a kick-off meeting for the center on Oct. 16 at noon at University Park for researchers across the University to learn more about the center, including new efforts in mathematical modeling, artificial intelligence (AI) and other computational technologies, as well as collaboration opportunities.
“The scientific study of living things is increasingly quantitative, exposing new opportunities for innovative research and interdisciplinary collaboration,” said Christina Grozinger, director of the Huck Institutes of the Life Sciences. “This center draws on Penn State's considerable strengths in an array of disciplines — with a common theme of using mathematical, statistical and computational tools to provide insight and understanding to biological observations and data analysis, which Wenrui is strongly positioned to lead. He has incredible expertise in bringing together scientists from across disciplines to tackle complex challenges, and I am so excited to see where he takes the Center for Mathematical Biology and Penn State in the coming years.”
Hao, who joined Penn State in 2016 as an assistant professor after earning a doctorate in applied mathematics from the University of Notre Dame, focuses his research on health-related computational modeling: digital twin modeling, where he creates a dynamic virtual model of a patient or group of people to simulate disease progression in order to analyze and improve potential treatment options; virtual clinical trials, using digital tools and technologies to recruit participants, collect data and monitor outcomes without requiring in-person visits; personalized treatment predictions for Alzheimer’s disease; and data-driven computational modeling of aneurysms.