肖燕妮, 西安交通大学数学与统计学院副院长、数学与生命科学交叉研究中心主任、博士生导师，主要从事数据和问题驱动的传染病动力学的研究。 参与完成了国家“十一五”、“十二五”和“十三五”科技重大专项艾滋病领域的建模研究。 主持国家自然科学基金多项，包括重点项目1项、重点国际合作1项，主持科技部重点研发课题1项。担任国务院第八届学科评议组成员（数学），2022年至今任中国生物数学专业委员会主任。

报告摘要：Accurate prediction of epidemics is pivotal for making well-informed decisions for the control of infectious diseases, but modelling heterogeneity in the system becomes a challenge. In this talk, we propose a novel modelling framework integrating the spatio-temporal heterogeneity of susceptible individuals into homogeneous models, by introducing a continuous recruitment process for the susceptibles. Then, a general human heterogeneous disease model with mutation is proposed to comprehensively study the effects of human heterogeneity on basic reproduction number, final epidemic size and herd immunity. We show that human heterogeneity may increase or decrease herd immunity level, strongly depending on some convexity of the heterogeneity function.  Finally, we illustrate how to link the deep learning to dynamic model to examine time-dependent transmission rate or the intensity of interventions.