• 1、基于数智融合的管内外流耦合动力学研究（国家自然科学基金项目），2024-2027。
• 2、数据驱动与知识驱动融合的智能流体力学（同济大学学科前沿交叉-智能建造项目），2022-2024。
• 3、基于机器学习和数字孪生驱动的海洋细长柔性结构健康监测系统（上海市人工智能学科交叉联合攻关项目），2021-2022 。
• 4、自立式消能减震墙钢结构体系（国家重点研发计划子课题），2017-2021。
• 5、钢桥构造细节随机疲劳损伤多尺度演化及预测研究（上海市自然科学基金项目），2017-2020。
• 6、装配式结构整体性检测评价技术（国家重点研发计划子课题），2016 -2020。
• 7、磁浮道岔梁振动疲劳寿命预测不确定性研究（科技部国家重点实验室基础研究项目），2014-2017。
• 8、基于证据理论和Info-Gap决策的结构可靠性稳健设计优化（国家自然科学基金项目），2012-2015。
• 9、基于证据理论的结构可靠性稳健设计优化研究（科技部国家重点实验室基础研究项目），2011-2013。
• 10、基于群集智能的复杂结构系统分散化识别方法研究（国家自然科学基金项目），2008-2010。

1. 1、Yangyang Liao, Yajuan Xie, Hesheng Tang*, Zihan Xia, Songtao Xue, A modal transfer enhanced deep learning for structural dynamic response with sparse spatial data, Engineering Applications of Artificial Intelligence, Volume 161, Part B, 2025, 112218, https://doi.org/10.1016/j.engappai.2025.112218.

• 2、Peng M, Tang H*,Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities, Communications Engineering 4, 150 (2025). https://doi.org/10.1038/s44172-025-00476-5.
• 3、Yangyang Liao, Tang H*, Liyu Xie, A deep modal model for reconstructing the VIV response of a flexible cylinder with sparse sensing data, Ocean Engineering,326( 2025),120871, https://doi.org/10.1016/j.oceaneng.2025.120871.
• 4、Mingsheng Peng, Tang H*, Yingwei Kou, Adversarial and self-adaptive domain decomposition physics-informed neural networks for high-order differential equations with discontinuities, Engineering Applications of Artificial Intelligence,145(2025), 110156, https://doi.org/10.1016/j.engappai.2025.110156.
• 5、Zhang, L., Tang H*, Xie, L. et al. On the fluid inerter with piecewise nonlinearity for enhanced vibration isolation. Nonlinear Dyn (2025). https://doi.org/10.1007/s11071-025-10927-5.
• 6、Xie Y, Tang H*. Low-supervised domain-adversarial neural network for cross-domain mooring line failure detection. Applied Ocean Research,149(2024),104066.
• 7、Xie Y, Tang H*. A deep learning approach based on domain generalization for mooring tension prediction in floating structures. Ocean Engineering, 306(2024),118128.
• 8、Liao Y , Tang H* , Li R ,et al.Seismic response prediction and parameters estimation of the frame structure equipped with the base isolation-fluid inerter system (FS-BIFI) based on the PI-LSTM model.Engineering Structures, 2024, 309.DOI:10.1016/j.engstruct.2024.118077.
• 9、Xie Y, Tang H*, Low YM.Deep gated recurrent unit networks for time-domain long-term fatigue analysis of mooring lines considering wave directionality. Ocean Engineering, 284 (2023),115244.
• 10、Tang H*, Xie Y. Deep transfer learning for connection defect identification in prefabricated structures. Structural Health Monitoring. 2023;22(3):2128-2146. doi:10.1177/14759217221119537.

AI4Science is a core group of faculty in DDMS focusedon the intersection of AI+SCIENCE. Our mission is to leverage scientific insightto develop new machine learning methods, and to develop and leverage newmachine learning methods to advance science.

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