Dr. Chang has served as the principal investigator for over 140 projects, primarily focusing on the development of pioneering methodologies and intelligent systems to address urban traffic congestion, enhance traffic safety, and mitigate the environmental impacts of fuel consumption and emissions. With sustained support from USDOT and MDOT), Dr. Chang has made well-recognized contributions to the nation's preeminent transportation research program, Intelligent Transportation Systems (ITS).Notably, Dr. Chang's early work in adapting defense technologies for ITS development led to three consecutive years (1993-1995) of ITS research awards from Martin Marietta. His innovative design of unconventional intersections earned acknowledgment from the American Institute of Physics Institute in 2009 and was featured in a TV-Discovery special program titled "Unconventional Intersection Planning and Design, Science News Researcher Discoveries & Breakthroughs Inside Science." Furthermore, Dr. Chang has pioneered the development of the first-generation prediction system for incident duration and its impacts, earning the Outstanding Paper Award at the 17th ITS World Congress in 2010. His work on "dynamic variable speed control" was recognized as "The Best Research Project" by the Research and Innovative Technology Administration (RITA), USDOT, in 2011, surpassing more than 100 projects sponsored by all Tier-I University Research Centers. Under his leadership, the project, focused on preventing intersection rear-end collisions and angled crashes, has been widely adopted by MDOT, earning the "2016 High-Value Safety Project" award from the American Association of State Highway and Transportation Officials (AASHTO).Most recently, Dr. Chang's research on “A real-time detection system for quality assessment of traffic sensors,” implemented by MDOT in the Eastern Shore region, was recognized as "the top high-value safety supplemental project in 2023" by AASHTO. In 2022, he was honored with the "2022 D. Grant Mickle Award" by the Transportation Research Board in recognition of his innovative AI-based methodology to address data deficiencies in highway incident detection and prediction.