Dec 2023
Zoom Link here.
Abstract
The relentless progress in computing and communication technologies has inaugurated a transformative era in ground mobility, presenting unprecedented opportunities to address enduring challenges in ground transportation. This talk explores some recent breakthroughs in the realm of human-centric robotics and machine intelligence, focusing on their pivotal role in revolutionizing ground transportation. The fusion of vehicle connectivity and automation emerges as a cornerstone, holding the potential to reshape the transportation paradigm. The advent of smart mobility technologies, particularly vehicle-to-everything communications, has unlocked an unparalleled wealth of information. This information, when harnessed strategically, can usher in substantial enhancements in vehicle operational energy efficiency, roadway safety, and human acceptance. The talk delves into the intricate interplay of diverse elements, including physical insights into vehicle system characteristics, computational prowess, communication capabilities, and the nuanced modeling and prediction of human behavior. By seamlessly integrating these facets with theories of control, estimation, and optimization, a promising avenue opens up for crafting future mobility systems that are not only more efficient and safer but also engender trust among users. The presentation sheds light on ongoing research endeavors centered on various intelligent vehicles as a ubiquitous robotic system. These research activities collectively strive towards the overarching goal of cultivating efficient, safe, and trustworthy human-centric ground transportation.
Bio
Prof. 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 University and joined UT Austin as the Accenture Endowed Professor. He also garnered five years of full-time industrial 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, robotics, human-centric automation, and cyber-physical system applications. Prof. Wang’s research program has been funded by National Science Foundation (NSF), Office of Naval Research (ONR), Department of Energy, U.S. Department of Transportation, National Highway Traffic Safety Administration, Texas Department of Transportation, GM, Ford, Honda, Tenneco, Eaton, Ftech, Denso, and others. Dr. Wang is the author or co-author of more than 400 peer-reviewed publications including 198 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 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 Young Investigator Award. Prof. Wang is an IEEE Vehicular Technology Society Distinguished Lecturer, SAE Fellow, ASME Fellow, and IEEE Fellow.
Prof. Wang received his B.E. degree in Automotive Engineering and his first M.S. degree in Power Machinery and Engineering from 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.