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肖思男 Xiao，Sinan
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肖思男 Xiao，Sinan

  • 职称：副教授

  • 邮箱：sinanxiao@scut.edu.cn

  • 工作单位：吴贤铭智能工程学院

  • 邮政编码：510640

  • 毕业院校：西北工业大学航空学院

  • 办公室：

  • 最后学位：工学博士

  • 办公电话：

  • 导师类别：硕、博导

个人简介  

肖思男，毕业于西北工业大学，先后在德国斯图加特大学、德国于利希研究中心以及英国巴斯大学从事研究工作，现就职于华南理工大学吴贤铭智能工程学院，任副教授，主要研究方向为结构不确定性量化，结构可靠性分析与设计，贝叶斯机器学习等。主持了1项中德博士后奖学金项目，作为核心成员参与了1项德国科学基金会项目以及1项英国工程和自然科学研究委员会项目，共发表学术论文40余篇，以第一作者/通讯作者发表SCI学术论文20余篇(1区论文16篇)，H-index: 17，担任JCRQ1期刊Mathematics客座编辑，受邀参与了捷克科学基金会项目的评审。

肖思男博士目前主要研究兴趣包括：

  • 结构可靠性设计及风险分析：结合概率统计理论和结构(有限元)模型预测结构的可靠度，对结构进行可靠性优化设计，对相应的风险进行评估。

  • 贝叶斯不确定性量化：基于先验信息和观测数据，采用贝叶斯统计推断理论校准模型参数，量化结构参数及响应的不确定性，为智能化决策提供依据。

  • 贝叶斯实验设计：充分考虑先验信息的作用，将其融入实验设计和结果分析中，逐步更新模型，实现用较少的实验代价获取更多的信息。

  • 模型敏感性分析：量化模型参数对模型输出响应的的影响，深入了解模型(系统)输入变量与输出变量之间的关系，量化模型(系统)对不确定性因素的稳健性。

欢迎感兴趣的学生加入！学生专业背景(包含但不限于)：机械工程、力学、航空航天、土木工程、概率统计等。

工作经历  

  • 2024年9月 至 今，华南理工大学，广州，副教授

  • 2021年6月 至 2024年9月，巴斯大学，巴斯，英国，研究助理

  • 2020年2月 至 2021年3月，于利希研究中心，于利希，德国，博士后

  • 2018年8月 至 2021年1月，斯图加特大学，斯图加特，德国，博士后

教育经历  

  • 2013年9月-2018年3月，西北工业大学，西安，飞行器设计，博士研究生

  • 2009年9月-2013年7月，西北工业大学，西安，飞行器设计与工程，本科

研究领域  

  •    结构可靠性设计与风险分析

  • 贝叶斯不确定性量化

  • 贝叶斯实验设计

  • 模型敏感性分析

奖励奖项  

  • 2020 西北工业大学优秀博士论文

  • 2018 德意志学术交流中心奖学金

代表论文

  • 1. S. Xiao, W. Nowak (2024). Failure probability estimation with failure samples: An extension of the two-stage Markov chain Monte Carlo simulation. Mechanical Systems and Signal Processing. 212, 111300

  • 2. L. Chavez Rodriguez, A. González-Nicolás, B. Ingalls, T. Streck, W. Nowak, S. Xiao, & H. Pagel (2022). Optimal design of experiments to improve the characterisation of atrazine degradation pathways in soil. European Journal of Soil Science, 73(1), e13211

  • 3. S. Xiao, W. Nowak (2022). Reliability sensitivity analysis based on a two-stage Markov chain Monte Carlo simulation. Aerospace Science and Technology, 130, 107938.

  • 4. M. Hinze, S. Xiao, A. Schmidt, W. Nowak (2022). Experimental evaluation and uncertainty quantification for a fractional viscoelastic model of salt concrete. Mechanics of Time-Dependent Materials, 1-24.

  • 5. K. Cheng, Z. Lu, S. Xiao, S. Oladyshkin, W. Nowak (2022) Mixed covariance function kriging model for uncertainty quantification. International Journal for Uncertainty Quantification. 12(3), 17-30.

  • 6. S. Xiao, T. Xu, S. Reuschen, W. Nowak, & H.-J. Hendricks Franssen (2021). Bayesian inversion of multi-Gaussian log-conductivity fields with uncertain hyperparameters: An extension of preconditioned Crank-Nicolson Markov chain Monte Carlo with parallel tempering. Water Resources Research, 57, e2021WR030313.

  • 7. S. Xiao, T. Praditia, S. Oladyshkin, W. Nowak (2021). Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis. Applied Energy, 285, 116456.

  • 8. K. Cheng, Z. Lu. S. Xiao, X. Zhang, S. Oladyshkin, W. Nowak (2021). Resampling method for reliability-based design optimization based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing, 156, 107630.

  • 9. S. Xiao, S. Oladyshkin, W. Nowak (2020). Forward-reverse switch between density-based and regional sensitivity analysis. Applied Mathematical Modelling, 84, 377-392.

  • 10. S. Xiao, S. Oladyshkin, W. Nowak (2020). Reliability analysis with stratified importance sampling based on adaptive Kriging. Reliability Engineering & System Safety, 197, 106852.

  • 11. D. Erdal, S. Xiao, W. Nowak, O.A. Cirpka (2020). Sampling behavioral model parameters for ensemble-based sensitivity analysis using Gaussian process emulation and active subspaces. Stochastic Environmental Research and Risk Assessment, 34(11), 1813-1830.

  • 12. S. Xiao, Z. Lu (2020). Structural reliability analysis with conditional importance sampling method based on the law of total expectation and variance in subintervals. Journal of Engineering Mechanics, 146(1), 04019111.

  • 13. S. Xiao, S. Oladyshkin, W. Nowak (2019). Reliability sensitivity analysis with subset simulation: application to a carbon dioxide storage problem. IOP Conference Series: Materials Science and Engineering, 615, 012051.

  • 14. S. Xiao, S. Reuschen, G. Köse, S. Oladyshkin, W. Nowak (2019). Estimation of small failure probabilities based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing, 133, 106248.

  • 15. Y. Wang, S. Xiao, Z. Lu (2019). An efficient method based on Bayes’ theorem to estimate the failure-probability-based sensitivity measure. Mechanical Systems and Signal Processing, 115, 607-620.

  • 16. L. Xu, Z. Lu, S. Xiao (2019). Generalized sensitivity indices based on vector projection for multivariate output. Applied Mathematical Modelling, 66, 592-610.

  • 17. Y. Zhou, Z. Lu, S. Xiao, W. Yun (2019). Distance correlation-based method for global sensitivity analysis of models with dependent inputs. Structural and Multidisciplinary Optimization, 60, 1189-1207

  • 18. S. Xiao, Z. Lu, P. Wang (2018). Multivariate global sensitivity analysis based on distance components decomposition. Risk Analysis, 38(12), 2703-2721.

  • 19. S. Xiao, Z. Lu (2018). Global sensitivity analysis based on Gini’s mean difference. Structural and Multidisciplinary Optimization, 58(4), 1523-1535

  • 20. S. Xiao, Z. Lu, P. Wang (2018). Global sensitivity analysis based on distance correlation for structural systems with multivariate output. Engineering Structures, 167, 74-83.

  • 21. Y. Wang, S. Xiao, Z. Lu (2018). A new efficient simulation method based on Bayes' theorem and importance sampling Markov chain simulation to estimate the failure-probability-based global sensitivity measure. Aerospace Science and Technology, 79, 364-372.

  • 22. S. Xiao, Z. Lu, L. Xu (2018). Global sensitivity analysis based on random variables with interval parameters by metamodel-based optimization. International Journal of Systems Science: Operations & Logistics 5(3), 268-281.

  • 23. S. Xiao, Z. Lu (2018). Reliability analysis by combining higher-order unscented transformation and fourth-moment method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 4(1), 04017034.

  • 24. S. Xiao, Z. Lu, P. Wang (2018). Multivariate global sensitivity analysis for dynamic models based on energy distance. Structural and Multidisciplinary Optimization. 57(1), 279-291.

  • 25. P. Wang, Z. Lu, K. Zhang, S. Xiao, Z. Yue (2018). Copula-based decomposition approach for the derivative-based sensitivity of variance contributions with dependent variables. Reliability Engineering & System Safety, 169, 437-450

  • 26. S. Xiao, Z. Lu, P. Wang (2018). Multivariate global sensitivity analysis for dynamic models based on wavelet analysis. Reliability Engineering & System Safety, 170, 20-30.

  • 27. S. Xiao, Z. Lu (2017). Structural reliability sensitivity analysis based on classification of model output. Aerospace Science and Technology, 71, 52-61.

  • 28. S. Xiao, Z. Lu, L. Xu (2017). Multivariate sensitivity analysis based on the direction of eigen-space through principal component analysis. Reliability Engineering & System Safety, 165, 1-10.

  • 29. S. Xiao, Z. Lu, F. Qin (2017). Estimation of the Generalized Sobol’s Sensitivity Index for Multivariate Output Model Using Unscented Transformation. Journal of Structural Engineering, 143(5), 06016005.

  • 30. P. Wang, Z. Lu, S. Xiao (2017). A generalized separation for the variance contributions of input variables and their distribution parameters. Applied Mathematical Modelling, 47, 381-399.

  • 31. P. Wang, Z. Lu, S. Xiao (2017). Variance-based sensitivity analysis with the uncertainties of the input variables and their distribution parameters. Communication in Statistics- Simulation and Computation, 47(4), 1103-1125.

  • 32. S. Xiao, Z. Lu, L. Xu (2016). A new effective screening design for structural sensitivity analysis of failure probability with the epistemic uncertainty. Reliability Engineering & System Safety, 156, 1-14.

  • 33. S. Xiao, Z. Lu (2016). Structural Reliability Analysis Using Combined Space Partition Technique and Unscented Transformation. Journal of Structural Engineering, 142(11), 04016089.

研究专利  

  • 基于最优条件重要抽样法的结构失效概率的求解方法, 2022-11-04, 中国, ZL201811029879.7