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日期: 2022-10-14 点击:


时间:2022年10月15 9:00--11:30

Lecture 3 The catalyzing and integrating roles of mathematical sciences for optimal rapid response to public health emergencies



Speaker Bio

Professor Jianhong Wu, a fellow of the Royal Society of Canada, fellow of Canadian Academy of Health Sciences, University Distinguished Research Professor of York University, Canada Research Chair of Applied Mathematics, and Chang Jiang scholar visiting professor, is the co-editor-in-chief of Infectious disease modeling and Big data information analysis, and a member of the editorial boards of journals such as J. Mathematical Biology and IEEE Transactions on the Pattern Analysis and Machine Intelligence; serves as the Fields Institute Commissioned leader of Canada's National COVID-19 Pandemic Rapid Response Modeling Task Force and is a member of the Provincial (Ontario) and Federal (Canada) Modeling Expert Groups. He has published 8 monographs and more than 450 academic papers in Kluwer, AMS/Fields, Springer, Wiley, and other publishers. His research interests include dynamical systems, neural networks and pattern recognition, biomathematics, and epidemiology. He has won more than 10 academic achievement awards, including the Queen's Diamond Jubilee medal of Canada, a lifetime Fields Institute Fellow, the Outstanding Achievement Award for Canadian Chinese Professionals, and the Canadian New Pioneer Technology Award.

吴建宏教授,加拿大皇家学会院士、加拿大健康科学院院士,York大学终身杰出特聘教授,加拿大应用数学首席教授(Canada Research Chair),长江学者讲座教授。吴建宏教授是传染病建模和大数据信息分析的联合主编,同时是《J. Mathematical Biology》和《IEEE Transactions on the Pattern Analysis and Machine Intelligence》等期刊的编委会成员;担任菲尔兹研究所委托的加拿大国家COVID-19大流行快速响应建模工作组的负责人,是省(安大略省)和联邦(加拿大)建模专家组成员。在Kluwer、AMS/Fields、Springer、Wiley等出版社出版专著8 部,发表学术论文450多篇。研究方向包括动力系统、神经网络和模式识别、生物数学和流行病学。获得了包括加拿大女王钻石禧功勋章(Queen's Diamond Jubilee medal)、终身Fields Institute Fellow、加拿大华人专业人士杰出成就奖、加拿大新先锋科技奖等在内的10余项学术成就奖。


Complex hazards and systemic vulnerabilities are converging, leading to disruptive disaster and emergency events that can escalate in frequency and severity. The ongoing COVID-19 pandemic highlights the urgent need for transformative changes in concepts, models, technologies, policy, governance, and operational tools to identify and manage interconnected, systemic risks of disasters and emergencies. This talk will share some Canadian successes and lessons learnt during the three major public health emergencies (SARS, H1N1 pandemic influenza and the COVID-19 pandemic) of the century, with a critical review of the roles of mathematical sciences in creating academic-industrial-public partnership and trans-disciplinary training and research collaborations to inform rapid response to emerging public health emergencies.