1. 城市大型基础设施多源数据智能感知和智慧运维的平台及策略研究，绍兴市科技局，2024年，100 万元，项目负责人；

2. 城市大型基础设施智能感知与智慧运维策略研究，人工智能研究院开放基金，2024年，5万，项目负责人；

3. 基于相场法和物理信息神经网络的混凝土细观断裂破坏模拟研究，中国博士后科学基金会，2022年，8万，项目负责人。

部分第一作者与通讯作者论文：

[1] A Real-Time Welding Defect Detection Framework Based on RT-DETR Deep Neural Network. Liu, Gaoyang; Yang, Duanrui; Ye, Jun*; et al. 2025. Advanced Engineering Informatics. （中科院1区Top）

[2] DF-CDM: Conditional Diffusion Model with Data Fusion for Structural Dynamic Response Reconstruction. Shu, Jiangpeng; Yu, Hongchuan; Liu, Gaoyang*; et al. 2025. Mechanical Systems and Signal Processing. （中科院1区Top）

[3] Three-Dimensional Slope Stability Analysis Using Independent Cover Based Numerical Manifold and Vector Method. Liu, Gaoyang; Zhuang, Xiaoying*; Cui, Zhouquan. 2017. Engineering Geology. （中科院1区Top）

[4] Two-Stream Boundary-Aware Neural Network for Concrete Crack Segmentation and Quantification. Liu, Gaoyang*; Ding, Wei; Shu, Jiangpeng; et al. 2023. Structural Control and Health Monitoring. 

[5] A Transformer Neural Network Based Framework for Steel Defect Detection under Complex Scenarios. Liu, Gaoyang; Chen, Yi; Ye, Jun*; et al. 2025. Advances in Engineering Software.

[6] Post-Earthquake Inspection of High-Speed Railway Viaducts with Multi-Scale Task Interaction Deep Learning Strategy. Shu, Jiangpeng; Yang, Han; Liu, Gaoyang*; et al. 2024. Advances in Structural Engineering.

[7] Proposing an Inherently Interpretable Machine Learning Model for Shear Strength Prediction of Reinforced Concrete Beams with Stirrups. Shu, Jiangpeng; Yu, Hongchuan; Liu, Gaoyang*; et al. 2024. Case Studies in Construction Materials.

[8] Prediction of Compressive Strength of Concrete under Various Curing Conditions: A Comparison of Machine Learning Models and Empirical Mathematical Models. Sun, Bochao; Huang, Yuxiang; Liu, Gaoyang*; et al. 2024. Innovative Infrastructure Solutions.

[9] Enhancing Concrete Frost Resistance Prediction with an Explainable Neural Network. Sun, Bochao; Zheng, Haoyang; Liu, Gaoyang*; et al. 2024. Case Studies in Construction Materials.

[10] BO-Stacking: A Novel Shear Strength Prediction Model of RC Beams with Stirrups Based on Bayesian Optimization and Model Stacking. Shu, Jiangpeng; Yu, Hongchuan; Liu, Gaoyang*; et al. 2023. Structures.

[11] A Hybrid Strategy of AutoML and SHAP for Automated and Explainable Concrete Strength Prediction. Sun, Bochao; Cui, Wenjun; Liu, Gaoyang*; et al. 2023. Case Studies in Construction Materials.

[12] Concrete Compressive Strength Prediction Using an Explainable Boosting Machine Model. Liu, Gaoyang; Sun, Bochao*. 2023. Case Studies in Construction Materials.

[13] Data-Driven Shear Strength Prediction of FRP-Reinforced Concrete Beams without Stirrups Based on Machine Learning Methods. Yang, Yuanzhang; Liu, Gaoyang*. 2023. Buildings.

[14] Data Anomaly Detection for Structural Health Monitoring Using a Combination Network of GANomaly and CNN. Liu, Gaoyang; Niu, Yanbo*; Zhao, Weijian; et al. 2022. Smart Structures and Systems.