报告人：Stanca Mihaela Ciupe

报告题目：How much data is needed to validate a multiscale model of viral infection?

时间：2025年4月29日 10:00-11:30

地点：兴庆校区北五楼427

摘要：

Uncertainty in parameter estimates from fitting mathematical models to empirical data limits the model’s ability to uncover mechanisms of interaction. Understanding the effect of model structure and data availability on model predictions is important for informing model development and experimental design. To address sources of uncertainty in parameter estimation, I will present several methodologies that can help determine when a model can reveal its parameters. I will apply them in the context of virus infections in animals and humans at within-host, population, and multiscale levels. Using these approaches, I will provide insight into the sources of uncertainty and provide guidelines for the types of model assumptions, optimal experimental design, and biological information needed for improved predictions.

报告人简介：

Dr. Stanca Ciupe is a professor of mathematics and Director of the Virginia Tech Center for the Mathematics of Biosystems. She received her Ph.D. in applied mathematics from the University of Michigan in 2005 and held postdoctoral positions at Los Alamos National Laboratories and Duke University. She is currently a visiting research fellow at Princeton University. Dr. Ciupe is an associate editor for Math Biosciences, the Journal of Theoretical Biology, and the Bulletin of Mathematical Biology and has published 46 scientific articles on mathematical virology, immunology, and epidemiology, appearing in journals such as the Proceedings of the National Academy of Science (USA), PLoS Computational Biology, the Bulletin of Mathematical Biology, the Journal of Theoretical Biology, and Proceedings of the Royal Society B. Dr. Ciupe has given invited scientific talk in many countries, including the United States, Canada, Germany, France, Spain, Japan, South Korea, UAE, Australia.

邀请人：肖燕妮 教授