A back analysis scheme for refined soil stratification based on integrating borehole and CPT data

- Xie, Jiawei, Zeng, Cheng, Huang, Jinsong, Zhang, Yuting, Lu, Jianlin

An explainable artificial intelligence approach for mud pumping prediction in railway track based on GIS information and in-service train monitoring data

- Zeng, Cheng, Zhao, Gouhan, Xie, Jiawei, Huang, Jinsong, Wang, Yankun

Back-Analysis of Slope GNSS Displacements Using Geographically Weighted Regression and Least Squares Algorithms

- Dai, Wujiao, Dai, Yue, Xie, Jiawei

Deep Bayesian survival analysis of rail useful lifetime

- Zeng, Cheng, Huang, Jinsong, Wang, Hongrui, Xie, Jiawei, Zhang, Yuting

Inferring Semi-Parametric Gaussian Process Model Parameters for Missing Geotechnical Data Prediction

- Xie, Jiawei, Huang, Jinsong, Zhang, Yuting

Integrating multiple sources of data for inhomogeneous soil profile

- Xie, Jiawei

Learning from prior geological information for geotechnical soil stratification with tree-based methods

- Xie, Jiawei, Huang, Jinsong, Griffiths, D. V.

A generic framework for geotechnical subsurface modeling with machine learning

- Xie, Jiawei, Huang, Jinsong, Zeng, Cheng, Huang, Shan, Burton, Glen J.

Development of two-dimensional ground models by combining geotechnical and geophysical data

- Xie, Jiawei, Huang, Jinsong, Lu, Jianlin, Burton, Glen J., Zeng, Cheng, Wang, Yankun

Rail Break Prediction and Cause Analysis Using Imbalanced In-Service Train Data

- Zeng, Cheng, Huang, Jinsong, Wang, Hongrui, Xie, Jiawei, Huang, Shan

Prediction of mud pumping in railway track using in-service train data

- Zeng, Cheng, Huang, Jinsong, Xie, Jiawei, Zhang, Bo, Indraratna, Buddhima

Settlement Predictions of a Trial Embankment on Ballina Clay

- Huang, Shan, Huang, Jinsong, Kelly, Richard, Zeng, Cheng, Xie, Jiawei

Systematic literature review on data-driven models for predictive maintenance of railway track: Implications in geotechnical engineering

- Xie, Jiawei, Huang, Jinsong, Zeng, Cheng, Jiang, Shui-Hua, Podlich, Nathan