Sue Ahn

Dr. Sue Ahn serves as a Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison, where she leads research in traffic flow theory, Intelligent Transportation Systems (ITS) applications, and traffic operational impacts on environment and safety. Her work bridges theoretical traffic dynamics with practical transportation solutions through quantitative analysis and ITS implementation.

Her academic foundation includes:

• PhD in Civil and Environmental Engineering, University of California, Berkeley (2005)
• MS in Civil and Environmental Engineering, University of California, Berkeley (2001)
• BS in Civil Engineering, Ohio State University (2000)

Dr. Ahn's research program focuses on three interconnected pillars: fundamental traffic flow understanding through observation and statistical methods; environmental and safety impact analysis of traffic phenomena; and development of traffic control strategies using ITS. Her expertise spans traffic flow modeling, adaptive traffic control systems, emissions quantification, and connected/automated vehicle integration, with recent work emphasizing machine learning applications in mixed-traffic environments. She translates theoretical insights into practical transportation management tools while maintaining rigorous scientific methodology.

Analysis of her 2023-2024 publications reveals dominant themes in connected/automated vehicle control (70% of output), traffic flow theory advancements (20%), and environmental impact assessment (10%). Key methodological trends include deep learning integration (LSTM networks, graph neural networks), stochastic behavioral modeling, and multi-dimensional trajectory optimization – reflecting the field's shift toward data-driven solutions for heterogeneous traffic systems.

Dr. Ahn's scientific recognition includes:

• 2023 Transportation Research Board Greenshields Prize (Best Paper Award)
• 2020 University of Wisconsin-Madison Vilas Associate award
• 2019 Transportation Research Board Best Paper in Traffic Flow Theory
• 2016 Transportation Research Board Cunard Award
• 2012 NSF CAREER Award
• 2008 Annual ITS Arizona Conference Best ITS Planning Project

She actively mentors graduate researchers through CIV ENGR 890 (Pre-Dissertator's Research) and CIV ENGR 990 (Thesis) courses, with her NSF CAREER grant providing foundational support for traffic flow theory investigations. Current advising focuses on automated vehicle behavior modeling and environmental impact quantification, while future work appears directed toward heterogeneous traffic management frameworks and real-world ITS deployment validation.