Dr. Xiao is an Associate Professor at the Department of Civil Engineering, Shanghai Jiao Tong University. His research interests include geotechnical risk and reliability, urban resilience and AI-powered hazard prevention, landslide hazard chain, etc. Several MSc, PhD, and postdoctoral positions are available. Candidates with backgrounds in civil engineering, hydraulic engineering, engineering geology, or data science are highly preferred. Interested applicants are welcome to contact Dr. Xiao via email (xiaote@sjtu.edu.cn) and visit the homepage (https://shortxiaote.github.io) for more details about the research group.

Education Background

2013–2018, PhD in Hydraulic Structure Engineering, Wuhan University

2009–2013, BSc in Water Conservancy and Hydropower Engineering, Wuhan University

Work Experience

2024–present, Associate Professor, Shanghai Jiao Tong University

2021–2023, Research Assistant Professor, Hong Kong University of Science and Technology

2018–2021, Postdoctoral Research Fellow, Hong Kong University of Science and Technology

Geotechnical risk and reliability

Urban resilience and AI-powered hazard prevention

Landslide hazard chain

Risk-informed decision-making

Intelligent and digital geotechnics

Offshore geotechnics

Assistant Editor & Editorial Board Member, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards

Member, CNISDE Technical Committee on Digital Disaster Reduction

Member, ASCE Geo-Institute Embankments, Dams, and Slopes Committee

Member, Youth Committee of Risk and Insurance Research Branch of China Civil Engineering Society

Corresponding Member, ISSMGE Technical Committees TC304 (Risk) / TC309 (Machine Learning) / TC222 (Digital Twin)

NSFC Excellent Young Scientists Fund (Overseas), PI, 2025–2027

NSFC General Program, AI agent for landslide risk decision-making in reservoir areas based on intelligent computation of landslide movement, PI, 2027–2030

NSFC Young Scientists Fund, Methods for regional landslide spatiotemporal prediction and risk-informed early warning using incomplete data, PI, 2025–2027

RGC Theme-based Research Scheme, Digital twin-empowered landslide emergency risk management, Co-I, 2024–2028

NSFC-RGC Joint Research Scheme, Evolution of landslide hazard chains triggered by strong earthquakes and the associated dynamic risk management, Co-I, 2021–2024

Consulting Project for Geotechnical Engineering Office of HKSAR Government, Uncertainties and target reliability of slopes, Co-I, 2023–2024

Publish over 50 SCI-indexed journal papers and one monograph.

Google Scholar: https://scholar.google.com/citations?user=blUFYi4AAAAJ

ResearchGate: https://www.researchgate.net/profile/Te-Xiao-2

Monographs

[1] Zhang, J., Xiao, T., Ji, J., Zeng, P., Cao, Z. J. (2023). Geotechnical Reliability Analysis: Theories, Methods and Algorithms. Springer, Singapore. 310p.

Representative Papers

[1] Xiao, T., Zhang, L. M.*, Cheung, R. W. M., Lacasse, S. (2023). Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques. Géotechnique, 73(9), 749-765.

[2] Xiao, T., Zhang, L. M.* (2023). Data-driven landslide forecasting: methods, data completeness, and real-time warning. Engineering Geology, 317, 107068.

[3] Ju, L. Y., Xiao, T.*, He, J., Wang, H. J., Zhang, L. M. (2022). Predicting landslide runout paths using terrain matching-targeted machine learning. Engineering Geology, 311, 106902.

[4] Xiao, T., Li, D. Q.*, Cao, Z. J., Zhang, L. M. (2018). CPT-based probabilistic characterization of three-dimensional spatial variability using MLE. Journal of Geotechnical and Geoenvironmental Engineering, 114(5), 04018023.

[5] Xiao, T., Li, D. Q.*, Cao, Z. J., Au, S. K., Phoon, K. K. (2016). Three-dimensional slope reliability and risk assessment using auxiliary random finite element method. Computers and Geotechnics, 79, 146-158.

[6] Zhou, H., Xiao, T.*, Zhang, L. L. (2026). Coupled and decoupled aero-hydro-geotech reliability analyses of monopile-supported offshore wind turbines considering multi-source uncertainty propagation. Ocean Engineering, 366, 127838.

[7] Zhao, F., Zhang, L. L., Xiao, T.*, Chen, Y. (2025). An equivalent state method for submarine spread modeling subject to hydrate dissociation. Engineering Geology, 352, 108070.

[8] Zhang, L. M.*, Xiao, T., He, J., Chen, C. (2019). Erosion-based analysis of breaching of Baige landslide dams on the Jinsha River, China, in 2018. Landslides, 16(10), 1965-1979.

[9] Li, D. Q.*, Xiao, T., Zhang, L. M., Cao, Z. J. (2019). Stepwise covariance matrix decomposition for efficient simulation of multivariate large-scale three-dimensional random fields. Applied Mathematical Modelling, 68, 169-181.

[10] Xiao, T., Li, D. Q.*, Zhou, C. B. (2025). Collaborative risk assessment approach in geotechnical engineering. Chinese Journal of Geotechnical Engineering, 47(7), 1335-1343. (in Chinese)

Undergraduate courses

CE3646: Artificial Intelligence Algorithms

Postgraduate courses

CE8019: Urban Resilience and AI-powered Hazard Prevention

Patent

Simulation method and system for soil hydro-mechanical coupling based on physics-informed neural networks, ZL202510619173.X

Software copyright

Nonintrusive geotechnical probabilistic analysis (NIGPA), 2017SR016335

Geotechnical spatial variability modeling and reliability analysis, 2014SR092563

National Excellent Young Scientists (Overseas), 2023

Shanghai Magnolia Talents (Youth), 2023

ISSMGE Bright Spark Lecture Award, 2023

HKIE Geotechnical Paper Award, 2024

Géotechnique Early Career Award, 2023

Georisk Best Paper Award, 2018

Georisk Most Cited Award, 2020

FOMLIG Excellent Paper Award, 2023

Outstanding Doctoral Thesis in Hydraulic Engineering, 2019