Jinghui Yuan is an R&D Staff in the Applied Research for Mobility Systems (ARMS) group at the Oak Ridge National Laboratory (ORNL). With a passion for advancing transportation technologies, his research spans various areas, including intelligent transportation systems, crash risk prediction, big data analytics, deep learning, traffic simulation, driving behavior modeling, and connected and automated vehicles (CAVs).

He earned his B.S. in civil engineering from Central South University in Changsha, China, in 2013. He continued his pursuit of knowledge at Tongji University in Shanghai, China, graduating with an M.S. in transportation planning and management in 2016. He earned his Ph.D. in transportation engineering from the University of Central Florida in 2019.

He is a senior member of IEEE. He also actively contributes to the transportation community as a young member of the ASCE Transportation & Development Institute (T&DI) transportation safety committee and an associate member of the ASCE T&DI Artificial Intelligence committee. He actively contributes as a peer reviewer for more than 20 reputable journals and conferences. He has authored and co-authored over 30 peer-reviewed journal publications, including notable journals such as TR-A, TR-C, TR-F, AAP, IEEE-ITS, IEEE-VT, and IEEE-IV.