On the prediction, evaluation, and simulation of epidemic dynamics of COVID-19
Webinar: https://yorku.zoom.us/j/98615589444?pwd=S1JYcVA0R291blBoZzBnRkhDdW56dz09 .
This talk will introduce several progresses that we have achieved recently in the investigation of the spreading dynamics of Covid-19. Using the machine learning framework, time-series analytic method, conventional epidemic model, an agent-based model, we have, respectively, studied the impacts of several factors and interventions on the spreading dynamics of Covid-19. All the studies show the great significance of the integration of the data-driven research with the model-driven research to address the prediction, evaluation, 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.
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