Jinghui Yuan

Jinghui Yuan

R&D Associate Staff

Jinghui Yuan is an R&D Associate Staff member 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 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, showcasing his commitment to advancing transportation science.

Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

  • R&D Associate Staff, Feb 2022 – Present
  • Postdoctoral Research Associate, Jun 2021 – Jan 2022

University of Central Florida, Orlando, Florida, USA

  • Postdoctoral Research Scholar, Aug 2019 – May 2021
  • Graduate Research Assistant, Aug 2016 – Aug 2019

Tongji University, Shanghai, China

  • Graduate Research Assistant, Aug 2013 – Jul 2016
  • Best Poster Award, The 19th IEEE International Conference on Mobile Adhoc and Smart Systems, IEEE MASS 2022, Oct 2022
  • DOE OTT Energy I-Corps Cohort 14 (Entrepreneurial Lead), Mar 2022
  • Best Paper Award (Second Place), China Journal of Highway and Transport, Dec 2019
  • Stage III Winner in the USDOT’s Solving for Safety Visualization Challenge, U.S. Department of Transportation, Nov 2019 (Lead algorithm developer)
  • Graduate Excellence Award, U.S.DOT University Transportation Center (SAFERSIM), Oct 2019