The Grainger College of Engineering
Illinois Center for Transportation

Data-friendly mesoscopic network modeling: Learning, prediction and decision-making

By Sean Qian on 02/27/2025 from 2:00 p.m. to 3:00 p.m. in 1611 Titan Dr., Rantoul, IL 61866

Join Sean Qian of Carnegie Mellon University as he presents via Zoom at the Spring 2025 Kent Seminar Series Thursday, February 27 from 2-3 p.m. (CT).

The Spring 2025 semester is set to feature 14 presentations, each addressing a topic related to autonomy in transportation. See the full lineup of speakers for Spring 2025 semester.

Pizza and soft drinks will be provided beginning at 1:30 p.m. in the ICT Classroom. 

All presentations will be held on Zoom, but some speakers will present in person at ICT.

Join Zoom Meeting
https://illinois.zoom.us/j/89890781073?pwd=CewiD3535GNiWvliWpS6nqBksMqnAE.1 

Meeting ID: 898 9078 1073
Passcode: 116680

Abstract and Bio

Emerging transportation data presents challenges in leveraging diverse spatio-temporal sources to understand travel patterns. This talk explores a mesoscopic network modeling framework for spatio-temporal passenger and vehicular flows in multimodal networks, addressing solo driving, public transit, parking, curb use and ride-sharing. Using a computational graph approach, machine learning techniques integrate data such as time-varying counts, speeds, census, transit and curb use to jointly learn travel behavior and network characteristics. The framework has been applied to optimize transportation planning for regions, cities and communities.


Qian is the H. John Heinz III Professor of Civil and Environmental Engineering at Carnegie Mellon University, where he also holds appointments at Heinz College of Information Systems and Public Policy and the Department of Electrical and Computer Engineering. He directs CMU’s Mobility Data Analytics Center and founded TraffiQure Technologies in 2020 to commercialize AI and machine learning in infrastructure and mobility services. His research focuses on dynamic network modeling and AI applications for multimodal transportation systems. Qian earned a doctorate in civil engineering from the University of California, Davis, in 2011, an M.S. in statistics from Stanford University in 2012 and was a postdoctoral researcher at Stanford from 2011 to 2013.