李勇祥博士围绕大规模复杂系统的质量与可靠性等风险评估理论，研究大数据与工程机理联合驱动的复杂系统不确定性分析与量化。研究方向主要包括试验设计与分析、统计与机器学习，统计质量控制、统计信号处理等数据科学方法与大数据技术。

[3] 国际运筹与管理科学学会(INFORMS)，会员
[2] 国际工业与系统工程学会(IISE)，会员
[1] 国际电气和电子工程师学会(IEEE)，高级会员

李勇祥博士围绕大规模复杂系统的质量与可靠性等风险评估理论，研究大数据与工程机理联合驱动的复杂系统不确定性分析与量化。研究方向主要包括试验设计与分析、统计与机器学习、统计质量控制、统计信号处理等数据科学方法与大数据技术。

主持项目：

1）上海市科学技术委员会浦江人才计划项目，21PJ1405500，基于多源异构传感的非恒定工况设备早期故障统计监测与智能诊断研究，2021-10 至 2023-09，30万元，结题，主持

2）国家自然科学基金委员会青年科学基金项目，72101147，基于多源异构数据多模态融合的复杂制造过程统计监测与智能诊断，2022-01-01至2024-12-31，30万元，在研，主持

3）上海市科学技术委员会"科技创新行动计划"自然科学基金面上项目，22ZR1431200，基于分布式数据融合的大规模代理模型研究，2022-04 至 2025-03，20万元，在研，主持

4）国家自然科学基金委员会面上项目，72471142，面向多阶段制造系统的可解释性跨模态智能质量管控，2025-01-01至2028-12-31，42万元，在研，主持

5）企业横向项目：无人机系统健康管理: 故障诊断与处理方案设计，10万元，结题，主持

参与项目：

1）Research Grants Council Project Theme-based Research Scheme (Hong Kong), T32-101/12-R, Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems（40,840,000 HKD）

2）General Research Fund (Hong Kong), 11272216, Statistical Monitoring of Multivariate Quality Profiles Using Correlated Gaussian Processes（676,000 HKD）

3）国家自然科学基金委青年科学基金项目，11301441：针对具有复杂特性计算机模型的试验设计 （22万元）

4）国家自然科学基金委面上项目，72072114：复杂数据环境下大规模风力发电场的功率预测、状态监控和故障诊断（48万元）

5）国家自然科学基金委员会面上项目，72171003，基于产品质量与设备状态联合建模的复杂制造系统监测与维护研究，2022-01-01至2025-12-31，48万元，在研，子任务（9.6万元）

6）科学技术部高技术研究发展中心国家重点研发计划青年科学家项目，2023YFB3307300，面向规模化生产过程的多源异构数据感知分析理论，2023-12 至 2026-11，200万元，在研，子课题（30万元）

22) Yongxiang LI, Yuanyuan LI, Di WANG*. (2025). Periodic Gaussian Process Controlled B-spline for Scalable Modeling of Irregularly Spaced Signals. IEEE Transactions on Information Theory. Accepted

21) Ruixian LI, Yongxiang LI, Yao CHENG*. (2025). Periodic Fractional Wiener Process for Degradation Modeling of Photovoltaic Systems. Technometrics. Accepted

20) Yongxiang LI, Wuyang ZHANG, Matthias Hwai Yong TAN, Peter CHIEN. (2025). Sequential Decomposition of Multiple Seasonal Components Using Spectrum-Regularized Periodic Gaussian Process. IEEE Transactions on Signal Processing. Accepted

19) Yongxiang LI, Yunji ZHANG, Qian XIAO*, Jianguo WU.  (2025). Noise Resistant Detection and Monitoring for Discriminating Periodicity and Correlation. Technometrics. Accepted.

18) Ruiyu XU, Chao WANG, Yongxiang LI, Jianguo WU*. (2025). Generalized Time Warping Invariant Dictionary Learning for Time Series Classification and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. Accepted

17) Di WANG, Andi WANG, Xiaochen XIAN, Yongxiang LI*. (2025). Partially Observable Online Nonparametric Monitoring of Spatiotemporally Correlated Data Streams. Technometrics. Accepted.

16) Xinming WANG, Yongxiang LI, Xiaowei YUE, Jianguo WU*. (2024). Non-stationary and Sparsely-correlated Multi-output Gaussian Process with Spike-and-Slab Prior. INFORMS Journal on Data Science. Accepted.

15) Ziyu LIU, Yongxiang LI*, Xiaowei YUE, Ershun PAN. (2024). Latent Functional Gaussian Process Incorporating Output Spatial Correlations.  IISE Transactions. Accepted.

14) Yongxiang LI, Yunji ZHANG, Jianguo WU*, Min XIE. (2024). Regularized Periodic Gaussian Process for Nonparametric Sparse Feature Extraction from Noisy Periodic Signals. IEEE Transactions on Automation Science and Engineering. Accepted.

13) Wei FAN, Fan JIANG, Yongxiang LI*, Zhike PENG. (2025). A Hankel Matrix-based Multivariate Control Chart with Shrinkage Estimator for Condition Monitoring of Rolling Bearings. IEEE Transactions on Automation Science and Engineering. 22, 293-304

12) Yongxiang LI, Qiang ZHOU*, Wei JIANG, Kwok-Leung TSUI. (2024). Optimal Composite Likelihood Estimation and Prediction for Distributed Gaussian Process Modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence.  46(2), 1134-1147.

11) Ruixian LI, Jianguo WU, Yongxiang LI*, Yao CHENG. (2024). PeriodNet: Noise-Robust Fault Diagnosis Method under Varying Speed Conditions. IEEE Transactions on Neural Networks and Learning Systems. 35(10), 14045-14059.

10) Yongxiang LI, Yunji ZHANG, Qian XIAO, Jianguo WU*.  (2023). Quasi-Periodic Gaussian Process Modeling of Pseudo-Periodic Signals. IEEE Transactions on Signal Processing. 71, 3548-3561.

9) Yushuai CHE, Yan MA, Yongxiang LI, and Linhan OUYANG*. (2023). A Novel Active-learning Kriging Reliability Analysis Method based on Parallelized Sampling Considering Budget Allocation. IEEE Transactions on Reliability. 73(1), 589-601.

8) Yongxiang LI, Yuting Pu, Qian XIAO*, Changming CHENG. (2023). A Scalable Gaussian Process for Large-Scale Periodic Data. Technometrics. 65(3), 363–374.

7) Wei FAN, Zhenqiang CHEN, Yongxiang LI*, Feng ZHU, Min XIE. (2023). A Reinforced Noise Resistant Correction Method for Bearing Condition Monitoring. IEEE Transactions on Automation Science and Engineering. 20(2), 995-1006.

6) Yongxiang LI, Yuting Pu, Wei FAN*, Jianguo WU. (2023). Constraint Linear Model for Period Estimation and Sparse Feature Extraction Based on Iterative Likelihood Ratio Test. IEEE Transactions on Industrial Electronics. 70(4), 4196-4205.

5) Ruiyu XU, Jianguo WU*, Xiaowei YUE, Yongxiang LI. (2023). Online Structural Change-point Detection of High-dimensional Streaming Data via Dynamic Sparse Subspace Learning. Technometrics. 65(1), 19-32.

4) Mithun GHOSH, Yongxiang LI, Qiang ZHOU*, Li ZENG, Zijun ZHANG. (2021). Modeling Multivariate Profiles Using Gaussian Process-Controlled B-Splines. IISE Transactions. 53(7), 787-798.

3) Wei FAN, Yongxiang LI*, Kwok-Leung TSUI, Qiang ZHOU. (2018). A Noise Resistant Correlation Method for Period Detection of Noisy Signals. IEEE Transactions on Signal Processing. 66(10) 2700-2710. 

2) Yongxiang LI, Qiang ZHOU*, Xiaohu HUANG, Li ZENG. (2018). Pairwise Estimation of Multivariate Gaussian Process Models with Replicated Observations: Application to Multivariate Profile Monitoring. Technometrics. 60(1), 70-78.

1) Yongxiang LI, Qiang ZHOU*. (2016). Pairwise Meta-Modeling of Multivariate Output Computer Models Using Nonseparable Covariance Function. Technometrics. 58(4), 483-494.