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Ph.D. Student

jingxiao liu

Ph.D. Student in Civil and Environmental Engineering, admitted Winter 2020
Ph.D. Minor, Electrical Engineering
Jingxiao Liu is a Ph.D. candidate in the Department of Civil & Environmental Engineering at Stanford University. He received his M.S. in Civil Engineering from Carnegie Mellon University in 2017. His research focuses on structural health monitoring, smart infrastructure systems, and smart city applications using signal processing, data mining, physics-guided machine learning, mobile sensing, and fiber-optic sensing techniques.

The main objective of his Ph.D. research is to develop physics-guided data-driven approaches for drive-by structural health monitoring that are scalable to a large stock of structures without requiring training data from every structure. His prior works on this topic have the following accomplishments: 1) Based on the physical understandings of vehicle-structure interaction systems, he has developed damage localization and quantification algorithms for drive-by SHM of bridges and an anomaly detection algorithm for railroad track geometry monitoring. He has published his works in top-tier conferences and journals in both civil and electrical engineering. 2) Collaborating with the Port Authority of Allegheny County, he has conducted real-world deployments and multiple field experiments on a light rail system, including a 42.2-km railroad track and multiple bridges, to validate the robustness of his approaches with complex and realistic infrastructure. He has published a comprehensive dataset collected from vehicles in this light rail system, which is the first open-access dataset for drive-by SHM.


M.S., Carnegie Mellon University, Civil Engineering (2017)