Resilience of Urban Infrastructure System
Urban infrastructure plays a fundamental role in maintaining the daily operation of a city. It encompasses the physical connections between places that facilitate the movement of people, information, materials, and energy, collectively known as the built environment. Additionally, it includes the social and economic infrastructure that supports crucial services such as healthcare, education, and other urban necessities. Unfortunately, urban infrastructure is vulnerable to various types of risks and uncertainties, including natural hazards and disasters like earthquakes and extreme weather events. The failure of these systems can have cascading and profound impacts on the city. Therefore, it is crucial to model, analyze, and optimize the resilience of such systems. Fortunately, emerging technologies such as machine learning and data-driven optimization approaches provide unprecedented opportunities for researchers to tackle this critical issue. This session will focus on the discussion of "Resilience of urban infrastructure system", exploring innovative approaches and strategies to address these challenges.
The list of topics includes, but is not limited to:
● Resilience modeling, optimization and analysis of urban infrastructure systems 城市基础设施系统的韧性建模、优化和分析
● Data-driven approaches in urban infrastructure resilience 在城市基础设施韧性方面的数据驱动方法
● Uncertainty modeling and analysis in resilience of urban infrastructure systems 城市基础设施系统韧性中的不确定性建模和分析
● Case studies in resilience of urban infrastructure systems 城市基础设施系统韧性的案例研究
Chair: Chunling Luo, Hangzhou Normal University, China
Chunling Luo is a professor at Department of Data Science and Management, Alibaba business school, Hangzhou Normal University, China. She received her PhD from the Department of Industrial Systems Engineering and Management at the National University of Singapore and her BEng in industrial engineering from Shanghai Jiao Tong University of China. Her research interests mainly include decision making under uncertainty (particularly in stochastic dominance), stochastic optimization, system modeling and optimization. (E-Mail: firstname.lastname@example.org)
罗春玲，杭州师范大学阿里巴巴商学院数据科学与管理系教授。新加坡国立大学博士，新加坡-麻省理工学院研究中心博士后。主要研究方向为不确定环境下的决策分析（随机占优理论）和运筹优化（随机优化和分布鲁棒优化），复杂系统建模和分析。主持国家自然科学基金青年基金项目、浙江省自然科学基金一般项目、杭州市哲学社会科学规划重点项目，在European Journal of Operational Research、Reliability Engineering & System Safety、Decision Analysis、Transportation Research Part C: Emerging Technologies等期刊发表多篇论文。
Chair: Lei Xu, George Tech Shenzhen Institute, Tianjin University, China
Lei Xu is an Assistant Professor at George Tech Shenzhen Institute, Tianjin University. She is also an Adjunct Assistant Professor at the Stewart School of Industrial & Systems Engineering at Georgia Tech. Dr. Xu’s research interests include resilience of transportation systems and humanitarian logistics. Dr Xu received the B.E. degree in Transportation Engineering from Shanghai Jiao Tong University, and Ph.D. degree in Industrial Engineering from National University of Singapore.
If you are interested in the special session, please submit
your paper or abstract here
https://www.zmeeting.org/submission/srse2023 and choose special session 12.
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