Assoc. Prof. Ziqiang Zeng
Management Science and System Science, Sichuan University
Data-driven decision making; multistage decision making and engineering optimization
Brief introduction of your research experience:
Dr. Ziqiang Zeng, is currently an Associate Professor at Business School of Sichuan University, and an Adjunct Professor at Silberman College of Business (AACSB Accredited), Fairleigh Dickinson University. He received the B.S. degree in applied mathematics and the Ph.D. degree in management science and engineering from Sichuan University, Chengdu, China, in 2009 and 2014, respectively, and was a Visiting Scholar at University of Florida, Gainesville, FL, USA, from 2012 to 2013. He has also been a Research Associate at University of Washington, Seattle, WA, USA, from 2016 to 2019. He has been selected as a Youth Talent of the Sichuan Provincial “Ten-Thousand Talents Program”, the Reserve Candidates for Academic and Technological Leaders in Sichuan Province, the Expert of Sichuan University “Double Hundred Talents Program”, the Sichuan Overseas High-Level Talent, and reported by Scientific Chinese as the “Back Cover Person”. He is an INFORMS Member, IEEE Member, ASCE Associate Member. He has published more than 40 peer-reviewed papers in journals, such as Risk Analysis, Scientometrics, IEEE Transactions on Fuzzy Systems, Computer-aided Civil and Infrastructure Engineering, Applied Energy, Renewable Energy, Accident Analysis and Prevention, and International Journal of Project Management. He has co-authored 3 books by Elsevier, Springer, and Sichuan University Press. He has been the principle investigator of more than 10 research projects, including a research project of US Department of Transportation, two projects from National Natural Science Foundation of China, the General Program of China Postdoctoral Science Foundation, and so on. He is also the Academic Editor of PLoS ONE, and the Evaluation Expert of National Natural Science Foundation of China. His current research interest includes data analysis and decision making, intelligent transportation systems, and system simulation and modeling.
Speech Title: Data-Driven Traffic Emission Analytic Platform for Chengdu City
Abstract: In recent years, China's regional atmospheric environmental problems have become increasingly prominent. It has become an important national strategy to control urban traffic pollution emissions and improve air quality. The construction of traffic emission big data analysis platform can realize low-cost real-time analysis and visualization of traffic emission data. It can also evaluate the environment and energy-saving benefits of traffic planning and decision-making, guide popular low-carbon travel, effectively promote the specific implementation of intelligent traffic management policy, eliminate the data barrier of industrial docking, promote the development of green transportation industry chain, revitalize the upstream and downstream resources of related industries, and bring new vitality to a city’s economy. Based on the data resources related to traffic emissions in Chengdu, this study constructed the basic framework and algorithm of the traffic emission big data analysis platform, and proposed the traceability analysis of traffic pollution emissions on road sections, that is, based on the road section emission prediction model, through big data analysis to locate possible high pollution road sections or regions, and dynamically analyze the formation, transmission and diffusion of traffic pollution emissions. On the basis of judging the formation of high pollution, this study further analyzes the causes and trends of high pollution, and provides a reliable basis for management decisions such as environmental accountability, punishment and rectification. Finally, from the perspectives of government, enterprises and publics, this study discusses the construction of ecological chain system of related data application.