Dai Quoc Tran is a research and development associate at Oak Ridge National Laboratory’s Energy Science and Technology Directorate. He is also a University of Tennessee-Oak Ridge Innovation Institute Fellow, working with the Institute’s Advanced Manufacturing for Affordable Building Construction Convergent Research Initiative.

Tran’s research interests include Automated Quality Control (AQC), multi-modal sensor fusion, and Edge-AI, with an emphasis on developing tracking systems and digital twins for advanced manufacturing and construction. He has coauthored more than 30 publications in the area of industrial AI and smart infrastructure, with an h-index of 15. His work has appeared in high-impact journals such as Automation in Construction, Advanced Engineering Informatics, and ASCE Journal of Construction Engineering and Management. He holds a U.S. patent for image-based environment variable learning systems.

In 2025, Tran served as a Postdoctoral Scholar at the University of Central Florida, contributing to the NSF Engineering Research Center for Smart Streetscapes (CS3). Prior to that, he was a Postdoctoral Scholar and Principal Investigator at Sungkyunkwan University (2023–2024) and an AI Team Lead at SmartInside AI Co., Ltd. (2021–2024), where he led government-funded projects on AI-based monitoring systems. In 2023, he participated in the KIC Tech Frontier Program at the University of California, Berkeley.

Tran’s technical capabilities have been recognized globally, achieving top rankings in premier computer vision challenges, including CVPR AICity, CVPR VizWiz, and ICCV. He is the recipient of multiple awards, including First Prize at the AI Championship in Korea (2022).

Education