Description:

Northwestern University Transportation Center presents:

"Low-rank modeling for spatiotemporal mobility and traffic data"

LIJUN SUN
Assistant Professor | Civil Engineering | McGill University

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Zoom Meeting (click to join):
https://northwestern.zoom.us/j/95235053776 

Meeting ID: 952 3505 3776

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Abstract:

Spatiotemporal mobility/traffic data, which registers timestamped travel activity/traffic state (e.g., flow and speed) observations from different locations (a network of sensors/zones), is an essential input to a wide range of intelligent transportation systems (ITS) and urban planning applications. These applications are critical components of smart transportation of the future, benefiting both travelers and transport agencies. The fundamental of modeling spatiotemporal mobility/traffic data is to characterize the spatiotemporal and higher-order correlations/dependencies within the data and perform efficient and reliable imputation/recovery/forecasting for decision making. However, traditional statistical models are computationally too costly to deal with the large-scale data sets we have. In this talk, I will focus on discussing the low-rank property of traffic and mobility data, and introducing recent development on low-rank modeling schemes for spatiotemporal mobility and traffic data. In particular, I will introduce some recent studies on traffic data imputation and traffic state estimation. 

Speaker Bio:

Dr. Lijun Sun is an Assistant Professor with the Department of Civil Engineering at McGill University, Montreal, Canada. He obtained his PhD degree in Civil Engineering (Transportation) from the National University of Singapore in 2015, and received his B.S. degree in Civil Engineering from Tsinghua University in 2011. Prior to joining McGill, he was a Postdoctoral Associate at MIT Media Lab during 2015-2017 and a Senior Researcher at Singapore-ETH Center in 2015. His research focuses on intelligent transportation systems and urban computing, developing innovative methodologies, tools, and applications to address the efficiency, resilience, and sustainability issues in urban transportation systems. He is now leading the Smart Transportation Lab (http://smart.lab.mcgill.ca/) at McGill, and the current research program of the lab centers on modeling large-scale, high-dimensional, and spatiotemporal urban mobility and traffic data. He is currently an Associate Editor of Transportation Research Part C: Emerging Technologies, and a member of the Editorial Advisory Board for Journal of Advanced Transportation. Dr. Sun’s research has been supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the Fonds de recherche du Québec – Nature et technologies (FRQNT), Fonds de Recherche du Québec - Société et Culture (FRQSC), Canada Foundation for Innovation (CFI), and the Institut de Valorisation des Données (IVADO).

Questions?  

Please contact Andrea Cehaic: andrea.cehaic@northwestern.edu 

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Zoom Meeting (click to join):
https://northwestern.zoom.us/j/95235053776 

Meeting ID: 952 3505 3776

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Meeting ID: 952 3505 3776