Speaker: Dr Wei Lin, Fudan University, China

Abstract: This talk will introduce the progresses that we have achieved recently in the investigation of the spreading dynamics of Covid-19.  Using a machine learning framework, including time-series analytic methods, conventional epidemic models, and agent-based models, we have, respectively, studied the impacts of several factors and interventions on Covid-19 transmission dynamics. All of our studies have shown the the great significance of the integration of the data-driven research with the model-driven study to address the prediction, evaluation, and simulation problems of epidemiology.  

Bio: Dr. Lin is a Full Professor in applied mathematics at Fudan University.  Currently, he is serving as the Dean of the Research Institute of Intelligent Complex Systems, and as the Director of the Centre for Computational Systems Biology and the Vice Dean of the ISTBI, Fudan University, China.  Now, he is acting as an AE of the IJBC, and a member of Editorial Advisory Board of CHAOS.  His current research interests include bifurcation and chaos theory, stochastic systems and complex networks, data assimilation, causality analysis, and their applications to systems biology and artificial intelligence.