讲座:Analytics Going Wild: Learning and Management of Wildlife 发布时间:2024-12-05
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- 主讲人:
题 目:Analytics Going Wild: Learning and Management of Wildlife
嘉 宾:Jue Wang, Associate Professor, Queen's University
主持人:花成 副教授 开云网页登录 安泰经济与管理学院
时 间:2024年12月12日(周四)9:30-11:00
地 点:安泰楼A507室
内容简介:
Ecosystems contribute to over half of the global GDP, but it is approaching a dangerous tipping point; wildlife populations have declined by 73% in the last 50 years, and half of the species are heading toward extinction in the next 100 years. A major challenge in biodiversity conservation is the scarcity of funding and information. As species populations decline, they become increasingly difficult to find. Collecting data is often costly and time-consuming, and high-stake decisions must be made based on small, low-quality data. Further, the species population can deteriorate rapidly, leading to extinction before sufficient data can be gathered. Therefore, how to allocate limited resources in a noisy, dynamic, and uncertain environment is a pressing challenge.
The scale, uncertainty, and spatial structure inherent in conservation demand innovations in decision science. In this talk, we use two case studies to illustrate the cross-fertilization between biodiversity conservation and partially observable Markov decision processes (POMDP). We will talk about the search and protection of Hainan gibbon (海南长臂猿), the rarest primate on earth, in the Hainan Tropical Rainforest National Park. We also explore the surveillance and management of a devastating wildlife disease, informally known as “zombie deer disease”, across North America. These projects are not possible without interdisciplinary, multi-institutional collaboration with conservation biologists, disease ecologists, and wildlife agency managers.
(Hainan gibbon,海南长臂猿)
演讲人简介:
Jue Wang (王珏) is an Associate Professor and Distinguished Faculty Fellow of Management Analytics at the Smith School of Business, Queen's University, Canada. His research focuses on wildlife operations research, where he develops models and algorithms to enhance decision-making in wildlife management. He collaborates closely with ecologists and wildlife managers around the world. He received his Ph.D. from the University of Toronto and is a visiting scholar at the SC Johnson School of Management, Cornell University. His work has been published in top journals, including Operations Research and Management Science. He has received several honors, including the New Researcher Achievement Award from Smith School of Business, the Canadian Operations Research Society Paper Competition, and the University of Toronto Early-Stage Technology Award.
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