Interested in joining the Smart Transportation Lab Team? If so, Research Assistant opportunities are currently available! If you are an M.S. or Ph.D. applicant, please see the official application process listed here. For more information, please click here.


If you are interested in an undergraduate research assistant position, please email me. An application is not required, but your CV is preferred. 

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Dr. Yao-Jan Wu is an associate professor of transportation engineering in the Department of Civil Engineering and Engineering Mechanics at the University of Arizona (UA) and the faculty adviser of the UA Institute of Transportation Engineers (ITE) student chapter. Before joining the UA, Yao was an assistant professor at Saint Louis University (2011~2013) and postdoc at the University of Virginia (2011). Yao received his Ph.D. degree from the University of Washington, Seattle in 2010. Currently, Dr. Wu is the director of the UA Smart Transportation Laboratory.

Dr. Wu has more than 100 referred publications, including more than 40 journal publications. He has presented his research findings more than 100 times at national and international conferences, and at invited speaker events. Dr. Wu's research interests highlight a strong connection between information technology (IT) and traditional transportation research.


My research interests highlight a strong connection between information technology (IT) and traditional transportation research. My research  covers four major fields:  1) intelligent transportation systems (i.e. development of advanced traffic detection technology and computer vision applications), 2) large-scale network analyses (i.e. online data management and analysis systems, network performance measurement and traveler behavior analysis), 3) traffic safety (i.e. accident modeling and analysis, and advanced safety vehicles), and 4) Sustainable transportation systems (e.g. climate change impact analysis). More specifically, my research interests are listed as follows: 

  • Intelligent transportation systems (ITS)

    • Image processing and computer vision applications

    • Traffic detection technology development

    • Advanced/information technology applications

  • Data-driven large-scale transportation system analysis and optimization

    • Freeway and arterial operations

    • Transportation system performance measurement

    • Big traffic data management, mining, and analysis

    • Travel behavior and pattern analysis

  • Transportation safety analysis and accident modeling

  • Sustainable transportation systems

    • Sustainable infrastructure

    • Transit system planning and operations

Courses Taught


Transportation Data Management and Analysis

An introduction to big traffic data management, database design, and statistical analysis.


Transportation Engineering and Pavement Design

A general introductory overview to transportation engineering concepts and applications


Traffic Engineering and Operations

An overview of several different transportation simulation topics and the technology behind traffic simulation

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