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chao shi

Assistant Professor

Nanyang Technological University Nanyang Technopreneurship Center

Singapore

Research Interests

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Professors in Geology

About

Chao Shi is an Assistant Professor at Nanyang Technological University, Nanyang Technopreneurship Center, Singapore. His research areas encompass geotechnical engineering, focusing on cement-rock interfacial bonding, long-term pile settlement prediction, and the application of large language models in geological data interpretation. Recent articles reflect his contributions to topics such as Bayesian compressive sensing, subsurface stratigraphy modeling, and thermomechanical behavior of energy piles.

Articles (30)

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2027

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2026

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2021

Collaborators (2)

Andy Yat Fai Leung

The Hong Kong Polytechnic University

HONG KONG

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Stephen Wu

Project assistant professor

The Institute of Statistical Mathematics

JAPAN

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chao shi

Research Interests

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Articles (30)

Physics-Informed online characterization of Mixed-Face geology along tunnel alignments integrating Multi-Source information

Investigation of Ultraclose Jet Grouting on Existing Cable Tunnel: Field Monitoring and Analytical Insights

Physics-Embedded Probabilistic Inverse Learning of Heterogeneous Consolidation Parameters from Sparse Multisource Data

A unified thermo-mechanical constitutive model for sand and clay based on hypoplasticity

Critical failure domain-informed smart sampling for slope stability assessment using Bayesian compressive sensing and reliability sensitivity analysis

Dual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests

Sparse representation of irregularly sampled geotechnical data for probabilistic gridded spatial interpolation using dictionary learning

Boolean stochastic stratigraphic modelling of geological cross-section from sparse cone penetration tests

Sequential sparse Bayesian learning of long-term thermomechanical performance of energy piles from limited multi-parameter monitoring data

Mechanism and performance of enhanced cement-rock interfacial bonding by metakaolin-based geopolymers under carbon sequestration conditions

Interpretable Ensemble Prediction of Thermally Induced Long-Term Pile Settlement from Limited Monitoring Data

Perspectives: LLM agents reshaping the foundation of geotechnical problem-solving

Few-shot learning of geological cross-sections from sparse data using large language model

Efficient basis-adaptive Bayesian compressive sensing with fast leave-one-out cross-validation for reliability analysis of geotechnical engineering systems

Influence of joint stiffness on three-dimensional deformation mechanisms of pipelines under tunnel active face instability

Nonparametric and continuous variable-based stratigraphic modelling from sparse boreholes using signed distance function and Bayesian compressive sensing

Physical and numerical investigation of deformation mechanisms of jointed pipelines due to passive face instability of EPB shield tunnelling

Field investigation on long-term deformation characteristics of long-and-narrow basements in soft clays

An ensemble learning paradigm for subsurface stratigraphy from sparse measurements and augmented training images

Numerical Investigation on Thermomechanical Behavior of Driven Energy Piles Subjected to Cyclic Thermal Loading in Sand

A BIM-based framework for automatic numerical modelling and geotechnical analysis of a large-scale deep excavation for transportation infrastructures

Machine learning of three-dimensional subsurface geological model for a reclamation site in Hong Kong

Data-driven sequential development of geological cross-sections along tunnel trajectory

Data-driven construction of Three-dimensional subsurface geological models from limited Site-specific boreholes and prior geological knowledge for underground digital twin

Assessment of Reclamation-induced Consolidation Settlement Considering Stratigraphic Uncertainty and Spatial Variability of Soil Properties

Effects of construction sequence of double basement excavations on an existing floating pile

Machine learning of geological details from borehole logs for development of high-resolution subsurface geological cross-section and geotechnical analysis

Training image selection for development of subsurface geological cross-section by conditional simulations

Smart Determination of Borehole Number and Locations for Stability Analysis of Multi-layered Slopes using Multiple Point Statistics and Information Entropy

Development of Subsurface Geological Cross-Section from Limited Site-Specific Boreholes and Prior Geological Knowledge Using Iterative Convolution XGBoost

Collaborators (2)

Andy Yat Fai Leung

Stephen Wu

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