Leveraging Integrated Vehicle-Traffic Systems for Efficient, Safe, and Trusted Automation


IEEE Vehicular Technology Society Distinguished Speaker Presentation

Recent advances in computing and communication technologies have ushered in a new era of ground mobility where vehicle connectivity and automation promise great potential to address some long-standing transportation challenges. In particular, smart mobility technologies such as vehicle-to-everything communications provided an unprecedented wealth of information that can be leveraged to enable substantial improvements on vehicle operational energy efficiency, roadway safety, and human acceptance. Synergistic combinations of physical insights into vehicle system characteristics, computational and communication capabilities, human user modeling and prediction, as well as theories of control, estimation and optimization may offer effective means of making future mobility systems more efficient, safer, and more trusted. This lecture introduces various vehicle automation systems research activities aiming at efficient, safe, and trustworthy human-centric ground transportation through collaboration and synergy among cyber systems, humans, and vehicles.

  Date and Time




  • Date: 08 Apr 2022
  • Time: 12:00 PM to 01:00 PM
  • All times are (GMT+10:00) Australia/Victoria
  • Add_To_Calendar_icon Add Event to Calendar

Please register for this event by using the registration button on the right and the Zoom event link will be sent to you a day before the meeting.

  • Starts 07 March 2022 11:58 AM
  • Ends 07 April 2022 11:59 PM
  • All times are (GMT+10:00) Australia/Victoria
  • No Admission Charge


Prof. Junmin Wang


Leveraging Integrated Vehicle-Traffic Systems for Efficient, Safe, and Trusted Automation

IEEE Vehicular Technology Society Distinguished Speaker


Junmin Wang is the Lee Norris & Linda Steen Norris Endowed Professor in Mechanical Engineering at the University of Texas at Austin. In 2008, he started his academic career at Ohio State University where he was early promoted to Associate Professor in September 2013 and very early promoted to Full Professor in June 2016. In 2018, he left Ohio State and joined UT Austin as the Accenture Endowed Professor.  He also gained five years of full-time industrial research experience at Southwest Research Institute (San Antonio Texas) from 2003 to 2008. Prof. Wang has a wide range of research interests covering control, modeling, estimation, optimization, and diagnosis of dynamical systems, especially for automotive, smart and sustainable mobility, human-centric automation, and cyber-physical system applications.  Prof. Wang’s research programs at UT-Austin and Ohio State University have been funded by federal agencies and industrial companies such as National Science Foundation (NSF), Office of Naval Research (ONR), Department of Energy (DOE), National Highway Traffic Safety Administration (NHTSA), Texas Department of Transportation, GM, Ford, Honda, Tenneco, Eaton, Ftech, Denso, and others. Dr. Wang is the author or co-author of more than 360 peer-reviewed publications including 185 journal articles and 13 U.S. patents. He is a recipient of numerous international and national honors and awards including 2019 IEEE Best Vehicular Electronics Paper Award, 2018 IEEE Andrew P. Sage Best Transactions Paper Award, 2017 IEEE Transactions on Fuzzy Systems Outstanding Paper Award, 2012 NSF-CAREER Award, 2011 SAE International Vincent Bendix Automotive Electronics Engineering Award, and 2009 ONR-YIP Award. He is an IEEE Vehicular Technology Society Distinguished Lecturer, SAE Fellow, and ASME Fellow. 
Dr. Wang received the B.E. in Automotive Engineering and his first M.S. in Power Machinery and Engineering from the Tsinghua University, Beijing, China in 1997 and 2000, respectively, his second and third M.S. degrees in Electrical Engineering and Mechanical Engineering from the University of Minnesota, Twin Cities in 2003, and the Ph.D. degree in Mechanical Engineering from the University of Texas at Austin in 2007. 


Address:Austin, Texas, United States