Rate My Professor Yao-Jan Wu

Wu founded and directs the Center for Applied Transportation Sciences (CATS) and the Arizona Transportation Institute (AZTI), partnering with the Arizona Department of Transportation, Arizona State University, and Northern Arizona University to tackle transportation challenges and workforce development. His research interests encompass intelligent transportation systems including advanced traffic detection and computer vision; data-driven analysis and optimization of large-scale transportation systems using big data for freeway and arterial operations and traveler behavior; traffic safety modeling; and sustainable transportation planning for transit, pedestrians, bikes, and climate change. He has authored or co-authored over 180 refereed publications, more than 80 journal articles, including recent works such as "Machine-learning approach for estimating passenger car equivalent factors using crowdsourced data" (2026, Transportmetrica A: Transport Science), "Data-driven transfer learning framework for estimating on-ramp and off-ramp traffic flows" (2025, Journal of Intelligent Transportation Systems), "Bayesian Deep Learning Approach for Real-Time Lane-Based Arrival Curve Reconstruction" (2025, IEEE Transactions on Intelligent Transportation Systems), and chapters like "Freeway to Arterial Interfaces" (2021). Wu has presented at over 100 conferences and holds editorial roles as associate editor of Transportation Research Record and editorial board member of Journal of Intelligent Transportation Systems. His awards include the LeadershipITE Fellow (2017), Outstanding Contribution in Reviewing for Transportation Research Part C (2018), and 2013-14 Professor of the Year from the department.