Sensitivity of ITS Learning Models with Mobility Data - applications in transportation privacy and cybersecurity
A Warren Distinguished Lecture with
Jeff Ban
Civil and Environmental Engineering
University of Washington
Abstract
Data is ubiquitous and data-driven models are widely deployed in intelligent transportation systems (ITS). So, issues related to data vulnerability, such as privacy and data security, are becoming more pressing in transportation. Central in addressing these vulnerabilities is understanding how sensitive ITS learning models are with respect to mobility data. Ban focuses on the specific features of ITS learning models and proposes an analysis framework for studying and measuring the sensitivity of ITS models with mobility data. He presents related concepts, measures, theories, and computational tools, which are tested using cybersecurity and privacy applications.
Speaker
Xuegang (Jeff) Ban is the William and Marilyn Conner Endowed Professor with the Department of Civil and Environmental Engineering at the University of Washington. He received his BS and MS in Automotive Engineering from Tsinghua University, and his MS in Computer Sciences and Ph.D. in Civil Engineering (Transportation) from the University of Wisconsin at Madison. His research interests are in Transportation Network System Modeling and Simulation, and Urban Traffic Modeling and Control. His recent work focuses on applying optimization, control, and ML/AI methods to the understanding and modeling of emerging technologies/systems in transportation such as Connected and Automated Vehicles, New Mobility Services, and electric buses. Ban is an Associate Editor of Transportation Research Part C, IEEE Transactions on Intelligent Transportation Systems, and Journal of Intelligent Transportation Systems. He received the 2011 CAREER Award from the National Science Foundation (NSF), and the New Faculty Award from the Council of University Transportation Centers (CUTC) and the American Road & Transportation Builders Association (ARTBA) in 2012. He was also one of the recipients of the Finalist for the Franz Edelman Award in 2017 by INFORMS.
