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。

Abstract

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.

复杂危害和系统的脆弱性正在汇聚，导致破坏性灾难和紧急事件的频率和严重性可能会升级。持续的新冠肺炎大流行突显出在概念、模型、技术、政策、治理和操作工具方面迫切需要进行变革，以识别和管理灾害和紧急情况中相互关联的系统性风险。本次演讲将通过回顾数学科学在创建学术-工业-公共伙伴关系和跨学科培训和研究合作中的作用，分享加拿大在本世纪三大公共卫生突发事件（SARS、H1N1大流行性流感和新冠肺炎大流行）中取得的一些成功的经验和吸取的教训，以帮助快速应对新出现的公共卫生突发事件。