[1] 国家重点研发项目子课题：地质储氢库适用性及安全关键技术，2024-12至2027-11，100万，在研,主持

[2] 湖北省重点研发专项课题：隧道结构运营安全智能预警与保障关键技术研究，2023-01至2025-12，25万，在研,主持

[3] 中国科学院特别研究助理资助项目：水下盾构隧道健康监测大数据驱动的结构力学行为研究，2022-01至2023-12，60万，结题,主持

[4] 中国科学院重点部署项目子课题：不良地质地下结构监测数据增强及异常性态辨识，2021-03至2024-3，100万，结题,主持

[5] 武汉英才-优秀青年人才项目：面向监测数据的水下盾构隧道力学响应预测与病害预警研究：2022-01至2023-12,20万,结题,主持

[1] Tan Xuyan,Palaiahnakote Shivakumara,Chen Weizhong,et al. A novel autoencoder for structural anomalies detection in river tunnel operation,Expert Systems with Applications,2024,244(2):122906.

[2] Tan Xuyan,Chen Weizhong,Tan Xianjun,et al. Prediction for the future mechanical behavior of underwater shield tunnel fusing deep learning algorithm on SHM data,Tunnelling and Underground Space Technology,2022,125: 104504.

[3] Tan Xuyan,Chen Weizhong,Zou Tao,et al. Real-time prediction of mechanical behaviors of underwater shield tunnel structure using machine learning method based on structural health monitoring data,Journal of Rock Mechanics and Geotechnical Engineering, 2022,15(4): 886-895.

[4] Tan Xuyan, Chen Weizhong, Wu Guojun, et al. A structural health monitoring system for data analysis of segment joint opening in an underwater shield tunnel, Structural Health Monitoring, 2019, 19(6): 1032-1050.

[5] Tan Xuyan, Chen Weizhong, Yang Jianping, et al. Prediction for segment strain and opening of underwater shield tunnel through deep learning method, Transportation Geotechnics, 2023, 39: 100928.

[6] Tan Xuyan, Sun Xuanxuan, Chen Weizhong, et al. Investigation on the data augmentation using machine learning algorithms in structural health monitoring information. Structural Health Monitoring, 2021,20(4): 2054-2068.

[7] Tan Xuyan, Wang Yuhang, Du Bowen, et al. Analysis for full face mechanical behaviors through spatial deduction model with real-time monitoring data. Structural Health Monitoring, 2022,21(4): 1805-1818.

[8] Tan Xuyan, Chen Weizhong, Gao Hou, et al. Overall sensing method for the three-dimensional stress of roadway via machine learning on SHM data. Structural Health Monitoring, 2023, 23(1): 175-186.

[9] Tan Xuyan, Tan Xianjun, Zhang Rui, et al. Identification of anomaly of tunnel segment strain using an adaptive machine learning model. Georisk, 2024, 18(4): 765-778

[10] Tan Xuyan, Chen Weizhong, Qin Changkun, et al. Characterisation for spatial distribution of mining induced stress through deep learning algorithm on SHM data. Georisk, 2023, 17(1): 217-226.

[11] Tan Xuyan, Chen Weizhong, Yang Jianping, et al. Temporal-spatial coupled model for multi-prediction of tunnel structure: using deep attention-based temporal convolutional network. Journal of Civil Structural Health Monitoring, 2022, 12: 675-687.

[14] Tan Xuyan, Chen Weizhong, Tan Xianjun, et al. Missing data imputation in tunnel monitoring with a spatio-temporal correlation fused machine learning model. Journal of Civil Structural Health Monitoring, 2024.

[12] Tan Xuyan, Chen Weizhong, Du Bowen, et al. Spatial characterization of strain variation in the profile of the tunnel structure using monitoring data and numerical modeling. ASCE-Journal of Infrastructure Systems, 2022. 28(3).

[13] Tan Xuyan, Chen Weizhong, Yang Jianping, et al. Application of a data-driven intelligent information system in infrastructure: underwater tunnel case study. ASCE-Journal of Performance of Constructed Facilities, 2022, 37(1).

[15] 谭旭燕，陈卫忠，杜博文，等. 数据驱动的水下盾构隧道衬砌应变行为预测研究，岩石力学与工程学报. 2022 ,41: 3317-3326.

中国岩石力学与工程学会科技一等奖（排3）

中国岩石力学与工程学会优秀博士学位论文奖