职称：讲师
学位：博士
研究方向为结构健康监测、数字孪生、贝叶斯推理、深度学习、混合驱动建模等。
1. 数字孪生建模
构建大跨桥梁和风力发电机数字孪生模型，基于贝叶斯模型修正、贝叶斯滤波法以及混合驱动建模方法，实现结构损伤识别、输入荷载（风荷载、交通荷载等）估计、结构响应预测等。
2. 物理-数据混合驱动建模方法
结合基于物理规律的建模方法（有限元模型、常/偏微分方程、状态空间方程等）和数据驱动建模方法（有监督学习、无监督学习、强化学习、对抗学习等），构建物理-数据混合驱动模型，提高模型预测精度、泛化能力和可解释性。
3. 贝叶斯系统识别
基于贝叶斯推理和层次贝叶斯方法，实现结构模态识别、模型修正、数据融合和不确定性量化；发展贝叶斯滤波和平滑理论，包含卡尔曼滤波、非线性滤波、高斯滤波、粒子滤波和RTS平滑法等，准确识别结构参数、荷载输入和系统状态。
相关网址：
桥梁系教师主页：https://bridge.tongji.edu.cn/45/53/c14930a279891/page.htm
桥梁健康监测与振动控制研究室主页：https://shmc.tongji.edu.cn/4f/de/c2302a282590/page.htm
ResearchGate: https://www.researchgate.net/profile/Mingming-Song-2
Google Scholar: https://scholar.google.com/citations?user=p_ryhTMAAAAJ&hl=en
1. 国家自然科学基金青年项目，基于层次贝叶斯理论和人工智能的桥梁结构混合数字孪生方法（编号52208199），2023.1 - 2025.12，主持
2. 上海市海外高层次人才项目，2022.3 – 2024.12，主持
3. 国家自然科学基金面上项目，基于混合监测的桥梁数字化建模（编号52378187），2024.1 - 2027.12，参与
4. 国家自然科学基金面上项目，基于多源残错数据的桥梁网级评估方法（编号52278313），2023.1 - 2026.12，参与
5. National Offshore Wind Research & Development Consortium, Physics Based Digital Twins for Optimal Asset Management (154719), 2021.1 - 2022.12, 80万美元, 参与
6. National Science Foundation (NSF), An Adaptive System Identification Approach Using Mobile Sensors (1903972), 2019.6 - 2022.5, 52万美元, 参与
7. Bureau of Safety and Environmental Enforcement (BSEE), The Block Island Structural Monitoring Joint Project (140E0119C0003), 2020.5 - 2021.12, 60万美元, 参与
8. United States Geological Survey (USGS), A Hierarchical Bayes Inversion Approach for Site Characterization Using Surface Wave Measurements (G18AP00034), 2018.6 - 2020.5, 8万美元, 参与
9. National Science Foundation (NSF), CAREER: Probabilistic Nonlinear Structural Identification for Health Monitoring of Civil Structures (1254338), 2013.6 - 2019.5, 40万美元, 参与
1. Song M, Mehr NP, Moaveni B, Hines E, Ebrahimian H, Bajric A. One year monitoring of an offshore wind turbine: Variability of modal parameters to ambient and operational conditions. Engineering Structures. 2023 Dec 15;297:117022.
2. Partovi-Mehr N, Branlard E, Song M, Moaveni B, Hines EM, Robertson A. Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions. Journal of Marine Science and Engineering. 2023 Jul 30;11(8):1524.
3. Song M, Moaveni B, Ebrahimian H, Hines E, Bajric A. Joint parameter-input estimation for digital twinning of the Block Island wind turbine using output-only measurements. Mechanical Systems and Signal Processing. 2023 Sep 1;198:110425.
4. Hines EM, Baxter CD, Ciochetto D, Song M, Sparrevik P, Meland HJ, Strout JM, Bradshaw A, Hu SL, Basurto JR, Moaveni B. Structural instrumentation and monitoring of the Block Island Offshore Wind Farm. Renewable Energy. 2023 Jan 1;202:1032-45.
5. Song M, Christensen S, Moaveni B, Brandt A, Hines E. Joint parameter-input estimation for virtual sensing on an offshore platform using output-only measurements. Mechanical Systems and Signal Processing. 2022 May 1;170:108814.
6. Mehrjoo A, Song M, Moaveni B, Papadimitriou C, Hines E. Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost. Mechanical Systems and Signal Processing. 2022 Apr 15;169:108787.
7. Song M, Renson L, Moaveni B, Kerschen G. Bayesian model updating and class selection of a wing-engine structure with nonlinear connections using nonlinear normal modes. Mechanical Systems and Signal Processing. 2022 Feb 15;165:108337.
8. Zhang Y, Lian J, Zhang G, Liu Y, Song M*, Li S. Ground vibration characteristics induced by flood discharge of a high dam: An experimental investigation. Journal of Renewable and Sustainable Energy. 2021 Jan 4;13(1):014502.
9. Liu P, Huang S, Song M, Yang W. Bayesian Model Updating of a Twin-Tower Masonry Structure through Subset Simulation Optimization Using Ambient Vibration Data. Journal of Civil Structural Health Monitoring. 2020 Oct 23:1-20.
10. Song M, Behmanesh I, Moaveni B, Papadimitriou C. Accounting for Modeling Errors and Inherent Structural Variability through a Hierarchical Bayesian Model Updating Approach: An Overview. Sensors. 2020 Jan;20(14):3874.
11. Song M, Astroza R, Ebrahimian H, Moaveni B, Papadimitriou C. Adaptive Kalman filters for nonlinear finite element model updating. Mechanical Systems and Signal Processing. 2020 Sep 1;143:106837.
12. Yousefianmoghadam S, Song M, Mohammadi M, Packard B, Stavridis A, Moaveni B, Wood RL, Packard B. Nonlinear dynamic tests of a reinforced concrete frame building at different damage levels. Earthquake Engineering & Structural Dynamics. 2020 May 11.
13. Song M, Behmanesh I, Moaveni B, Papadimitriou C. Modeling error Estimation and response prediction of a 10-Story building model through a hierarchical Bayesian model updating framework. Frontiers in Built Environment. 2019;5:7.
14. Song M, Moaveni B, Papadimitriou C, Stavridis A. Accounting for amplitude of excitation in model updating through a hierarchical Bayesian approach: Application to a two-story reinforced concrete building. Mechanical Systems and Signal Processing. 2019 May 15;123:68-83.
15. Song M, Renson L, Noël JP, et al. Bayesian model updating of nonlinear systems using nonlinear normal modes. Structural Control and Health Monitoring. 2018 Dec;25(12):e2258.
16. Song M, Yousefianmoghadam S, Mohammadi ME, Moaveni B, Stavridis A, Wood RL. An application of finite element model updating for damage assessment of a two-story reinforced concrete building and comparison with lidar. Structural Health Monitoring. 2018 Sep;17(5):1129-50.
