报告题目: Nonidentifiability in Parameter Estimation: what is it, why does it happen, and what can we do about it?

报告时间：2020年12月6日（周日）上午 10：00-12：00（北京时间）

腾讯会议：842 447 763， 密码: 1206

报告人： Prof. Michael Li，University of Alberta

报告摘要：

This talk is a general discussion about the challenges facing mathematical modelers when predicting real epidemics such as the COVID-19 pandemic. Differential equation based models is a wonderful tool, when there is no data involved. We develop ever more realistic models to discover new “insights” for the transmission and spread of diseases. When real epidemics occur, our models inevitably fail miserably. For instance, US CDC has been holding annual influenza model prediction contests for more than six years, and none of the winning model was differential equation based. As mathematicians, we need to ask and understand why does this happen. In this talk, I will ask questions to provoke everyone to think, and I will also report what our group has learned so far from modeling the COVID-19 epidemics.

报告人简介：

Michael Li is a Professor of Mathematics at the University of Alberta, Canada. His research interests the theory and applications mathematical modeling of infectious diseases in general, and of HIV, influenza and Tuberculosis in particular, viral dynamics and immune responses dynamics to viral infections including HIV-1 and HTLV-1. Professor Li obtained his PhD in Applied Mathematics at the University of Alberta and did his postdoctoral training at the University of Montreal and Georgia Institute of Technology. He has been a faculty member at the University of Alberta since 2000, where he actively collaborate with research groups in the faculty of medicine and at the Alberta Ministry of Health on modeling research in health and public health sciences.