Digital Twin Technologies in Transportation Infrastructure Management (PDF)

Engineering Research Center for High-Speed Railway Construction Technology, and a member of the Academic Committee of the Key Laboratory of High-Speed Railway Line Engineering of the Ministry of Education. Additionally, he is the Vice Chairman of the Hunan Provincial Highway Society and the Hunan Provincial Railway Society. Professor Wang has been dedicated to researching geological hazard zoning and intelligent construction technology for rail transit. He is an expert of profound expertise in intelligent monitoring for high-speed railways, geological hazard site selection, and digital twin technology for rail transit.

Chengbo Ai is an assistant professor at the University of Massachusetts Amherst, School of Civil and Environmental Engineering. He has long been working on artificial intelligence, intelligent detection of infrastructure injury and damage, and the construction of digital twin infrastructure models. Dr. Ai has published several high-level papers, has been invited to give many talks at international conferences, and is an expert in civil engineering.

Jin Wang is a postdoctoral researcher who earned his Ph.D. degree in Transportation Management Engineering from Beijing Jiaotong University. Currently, he is affiliated with the School of Civil Engineering at Central South University. For many years, he has been dedicated to research in operations research, digital visualization, simulation modeling, and algorithm design. He has profound expertise in parameterized infrastructure modeling and constructing digital twin models. Dr.Wang has published over 10 academic papers in high-level domestic and international journals such as "Computer-Aided Civil and Infrastructure Engineering" and "The Journal of Railway Science and Engineering." He has been granted 7 national invention patents.

Wang Sicheng is a Ph.D. candidate in the School of Civil Engineering, Central South University, and has long been devoted to the interdisciplinary research of computer and civil engineering disciplines, with in-depth research on the whole life cycle intelligent management of infrastructure, the reliability evaluation method of railroad four-electricity project, digital twin model of rail transportation, safety evaluation and disaster simulation of railroad slope, and research of railroad slope safety evaluation method, etc. He has a deep understanding of the digital twin of civil engineering.

Wenjuan Wang was born in Chongqing, China, in 1986, and received her Ph.D. degree in civil engineering from Oklahoma State University, OK, USA in 2015. She worked as a lecturer in the school of business administration at the Capital University of Economics and Business, Beijing, China from 2015 to 2018. She is an associate professor at the Capital University of Economics and Business, Beijing, China now. She has published many papers in top SCI journals including Computer-Aided Civil and Infrastructure Engineering, Journal of Transportation Engineering, Part B: Pavements, and so on.

Wenbo Hu has devoted himself to conducting cross-disciplinary research between computer information technology and traditional civil engineering detection and monitoring over an extended period. He possesses a comprehensive understanding of the potential of computer science to drive innovation in the civil engineering and transportation engineering domains. By establishing digital twin models, Mr. Hu manages infrastructure across its entire life cycle and on all scales, including the collection of high-precision, multidimensional infrastructure data obtained from sensors such as laser radars and cameras. His research efforts are focused on pattern recognition, machine learning, and deep learning techniques to attain artificial intelligence evaluations of infrastructure asset management and performance status and efficiency. He utilizes theoretical modeling and algorithmic advancements of various infrastructure real-time and spatial sensing data to support decision-making in the design, construction, operation, maintenance, and asset management of core subsystems of smart infrastructure, including rail transit, municipal services, and roads. Moreover, he has built an infrastructure equipment status evaluation and fault early warning big data analysis platform that leverages equipment portrait analysis technology.