2004-2008 香港科技大学 工业工程与工程管理专业 博士
2001-2004 南开大学 概率论与数理统计专业 硕士
1997-2001 南开大学 概率论与数理统计专业 学士

2008-至今 350vip8888新葡的京集团工业工程与物流管理系

1）复杂装备机理+数据驱动的智能预测、过程优化与监控、故障诊断与预测
2）多元时空数据的预测与建模
3）高维复杂数据的统计过程控制方法
研究结合汽车发动机、电子、新能源风机等制造业领域开展工程应用。

课题组2025年春季招收工业工程、机械、统计、数学等理工科背景博士研究生1名，欢迎邮件联系（ytli@sjtu.edu.cn）。

1. Faculty Advisor for SJTU-MIT International Joint Program-China Leaders for Manufacturing (CLFM) and SJTU-MIT International Joint Program-China Leaders for Global Manufaturing (CLGO)
2. 上海市质量金奖、市长奖文件评审专家（2015-）
3. 上海市经济和信息化委员会”质量标杆”专家（2017-）
4. 上海市质量技术应用统计学会理事（2017-）
5. 上海市质量协会质量技术奖项目评审专家（2018-）
6. 江苏省市场监督管理局“江苏省质量专家”（2019-2023）
7. Paper Reviewer for "Technometrics", "IIE Transactions”, "Journal of Applied Statistics”, “Journal of Quality Technology" and "Annals of Operations Research".

1.国家自然科学基金青年项目“多工序制造过程中离散型和混合型质量数据的统计过程监控方法研究”(70902070)。负责人。2010-2012。
2.国家自然科学基金面上项目“多元计数数据的统计过程控制方法研究”(71272003)，负责人。2013-2016。
3.国家自然科学基金面上项目“多元复杂时空数据建模与监控方法研究”(71672109)，负责人。2017-2020。
4. 国家自然科学基金面上项目“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”(72072114)，负责人。2021-2024。
5. 国家自然科学基金面上项目“多源大数据驱动的多风电场协同功率预测和运行监测研究”(72471139). 负责人。2025-2028。
6.国家重点研发计划项目，钢铁全流程多工序动态协同运行优化技术及示范应用，子课题负责人。 2020-2023。
7. 国家自然科学基金面上项目“质量管理中高维数据的统计过程控制研究”  (71172131)，研究骨干。2012-2015。
8. 国家自然科学基金重点项目“基于物联网的产品状态智能监控与质量管理”(71531010)，研究骨干。2016-2020。
9. 350vip8888新葡的京集团晨星学者奖励计划B类。负责人。2014-2016.
10. 面向冷轧薄板大数据的统计过程控制软件包开发，宝山钢铁股份有限公司。2021-2022，课题负责人.

部分代表性论文：
1. Li, Y. and Tsung, F. (2009). “False Discovery Rate-Adjusted Charting Schemes for Multistage Process Monitoring and Fault Identification”. Technometrics, 51, 186-205. (SCI, impact factor= 1.711).
2. Jin, M., Li, Y. and Tsung, F. (2010) “Chart Allocation strategy for Serial-Parallel Multistage Manufacturing Processes”. IIE Transactions, 42(8), 577-588. (SCI, impact factor= 1.287).
3. Han, D, Tsung, F. and Li, Y. (2010) “A Nonlinear Filter Control Chart For Detecting Dynamic Changes”. Statistica Sinica, 20, 1077-1096. (SCI, impact factor= 0.956).
4. Han, D. and Tsung, F. , Li, Y. and Xian, J. (2010) “Detection of Changes in a Random Financial Sequence with a Stable Distribution ". Journal of Applied Statistics, 37(7), 1089-1111. (SCI, impact factor= 0.407).
5. Li, Y. and Tsung, F. (2011). “Chart Allocation Strategy for Serial Parallel_Multistage Manufacturing Processes with Multiple Faults”. Journal of the Chinese Institute of Industrial Engineers, 28(7),493-503.(EI)
6. Li, Y. and Tsung, F. (2011) “Detecting and Diagnosing Covariance Matrix Changes in Multistage Processes”. IIE Transactions, 43(4), 259-274. (SCI, impact factor=1.287).
7. Li, Y. and Tsung, F. (2012). “Multiple Attribute Control Charts with False Discovery Rate Control”. Quality and Reliability Engineering International, 28(8), 857-871. (SCI, impact factor=0.700)
8. Li, Y.; Liu, Y.; Zou, C. and Jiang, W. (2014).A Self-Starting Control Chart for High Dimensional Short-run Process. International Journal of Production Research （中科院二区）, 52, 2, 445-461.(SCI, impact factor=1.460)
9. Li, Y.; Su,Y. and Shu, L.(2014). An ARMAX model for forecasting the power output of a grid connected photovoltaic system. Renewable Energy （中科院一区）. 66, 78-89. (SCI, impact factor=2.989)
10. Huang,W.,Jiang,W.,Wei, Q. and Li, Y. (2015).Projection-based Process Monitoring based on Empirical Divergence. IEEE Intelligent Systems Special Issue on System Informatics，IEEE Intelligent Systems,2015,30(6)：13-16..(SCI,impact factor=2.340)
11. Li, Y.; Shu,L. and Tsung, F.(2016). A False Discovery Approach for Scanning Spatial Disease Clusters with Arbitrary Shapes. IIE Transactions. Vol.48, No.7, 684-698.
12. Li, Y, Yong He, Yan Su, Lianjie Shu(2016).Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines, Applied Energy（中科院一区） , 180, 392–401.(SCI, impact factor=5.746)
13. Wang,Z., Li, Y.*, Zhou, X. (2017).A Statistical Control Chart for Monitoring High Dimensional Poisson Data Streams. Quality and Reliability Engineering International，33（2）,307–321. （SCI）
14. Li, Y. Liu, S. and Shu, L. (2018). Wind Turbine Fault Diagnosis Based on Gaussian Process Classifiers Applied to Operational Data. Renewable Energy （中科院一区）. 66:78–89. (impact factor=6.274)
15. Fan, Jinyu; Shu, LJ; Yang, AJ; Li, YT （2020） Phase I analysis of high-dimensional covariance matrices based on sparse leading eigenvalues. Journal of Quality Technology （中科院二区）. 2021, 53(4), 333-346. DOI: 10.1080/00224065.2020.1746212
16. Zhang, Y, Li, Y* and Zhang, GY(2020) Short-term wind power forecasting approach based on Seq2Seq model using NWP data. Energy（中科院一区） . 213, 15，118371 （impact factor=6.082）.
17. Li, Y. Pei, D. and Wu, Z. (2020) "A Multivariate Non-Parametric Control Chart Based on Run Test
Computers & Industrial Engineering" . Computers & Industrial Engineering （中科院二区）. 149, 106839。(impact factor=4.135)
18. Li, Y. Wu, Z. (2020) A condition monitoring approach of multi-turbine based on VAR model at farm level. Renewable Engergy （中科院一区）, 166, 66-80. (SCI, impact factor=2.989)
19.Li, Y. Jiang, W. Shu, L. (2021) Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data. Renewable Energy（中科院一区）, 171, June 2021, Pages 103-115.
20. Yanrong LI,Shizhe PENG,Yanting LI,Wei JIANG (2020). A review of condition-based maintenance: Its prognostic and operational aspects[J]. Frontiers of Engineering Management, 2020, 7(3): 323-334.
21. Lei Y, Li Y*. A novel scheme of domain transfer in document-level cross-domain sentiment classification. Journal of Information Science. May 2021. doi:10.1177/01655515211012329
22. Yanting Li*, Xinghao Peng, Yu Zhang(2022). Forecasting wind power scenarios of multiple wind farms based on vine spatiotemporal copula[J], Renewable Energy （中科院一区）, 201, 950-960.
23. Guangyao Zhang, Yanting Li* and Wenbo Jiang, et al. (2022) A fault diagnosis method for wind turbines with limited labeled data based on balanced joint adaptive network. Neurocomputing(中科院一区), Volume 481, Pages 133-153. DOI10.1016/j.neucom.2022.01.067
24. Zhenyu Wu, Yanting Li*. Lanye Hu.(2022) A Synchronous Multiple Change-point Detecting Method for Manufacturing Process[J]. Computers & Industrial Engineering (中科院一区), 169: 108114. https://doi.org/10.1016/j.cie.2022.108114
25. Songkang Wen, Yanting Li* and Yan Su (2022). A New Hybrid Model for Power Forecasting of a Wind Farm Using Spatial-Temporal Correlations[J]. Renewable Energy（中科院一区）, 198, 155-168
26. Peng Wang, Yanting Li*. （2023） Probabilistic power curve estimation based on meteorological factors and density LSTM. Energy (中科院一区)，269(15), 126768.
27. Zhenyu Wu, Li,Y*, Fugee Tsung, Ershun Pan (2023), Real-Time Monitoring and Diagnosis Scheme for IoT Enabled Devices using Multivariate SPC Techniques. IISE Transactions. 55(4). 348-362. https://doi.org/10.1080/24725854.2021.2000681.(中科院一区)
28. Wenpo Huang, Lianjie Shu, Yanting Li*. (2023) A Phase I Change-point Method for High-dimensional Process with Sparse Mean Shifts, Naval Research Logistics,70,261–273（中科院二区）https://doi.org/10.1002/nav.22095
29. Guangyao Zhang, Yanting Li*, et al (2023) A novel fault diagnosis method for wind turbine based on adaptive multivariate time-series convolutional network using SCADA data. Advanced Engineering Informatics. 57, 102031. (中科院一区)
30. Feng Xu, Lianjie Shu*,Yanting Li, Binhui Wang (2023), Joint Diagnosis of High-Dimensional Process Mean and Covariance Matrix based on Bayesian Model Selection, Technometrics，65(4), 465-479. https://doi.org/10.1080/00401706.2023.2182366. (中科院三区)
31. Yanting Li, Zhenyu Wu, Yan Su (2023) Adaptive short-term wind power forecasting with concept drifts. Renewable Energy, 217,119146. (中科院一区)
32. Zhenyu Wu, Yanting Li*, Peng Wang (2024) A hierarchical modeling strategy for condition monitoring and fault diagnosis of wind turbine using SCADA data. Measurement, 227, 114325.
(中科院二区)
33. Zhenyu Wu, Yanting Li. The Condition Monitoring Scheme for Industrial IoT Scenario: A Distributed Modeling for High-dimensional Nonstationary Data. Computers & Industrial Engineering. 2024.
34. Yanting Li, Peng Wang, Zhenyu Wu, Yan Su. Collaborative Monitoring of Wind Turbine Performance based on Probabilistic Power Curve Comparison. Renewable Energy. Vol. 231, September 2024, 120919.
35. Yanting Li, Yizhuo Cai, Short-term wind speed forecast based on dynamic spatio-temporal directed graph attention network. Applied Energy, 375, 2024, 124124.


【中文】
1. 何勇,李艳婷*（2017）基于向量自回归模型的移动通信基站流量预测[J].工业工程与管理,22(04)，79-84.
2. 娄璐，李艳婷*（2018）面向未知自相关过程的Bootstrap控制图设计，《工业工程》，21(4), 23-33.
3. 刘姝君,李艳婷*（2019）基于深度高斯过程的多元类别数据分布估计[J].计算机工程,45(2):160-166.
4. 龙威,李艳婷*（2019）基于多元泊松时间序列的累积和控制图设计[J].工业工程与管理,24(4):105-112.
5. 张乔威，李艳婷*（2019）基于R-Vine Copula的多维混合型数据控制图设计.工业工程，22（5）126-149。
6. 龙威,李艳婷*（2020）基于多元泊松模型的累积和控制图设计[J].应用概率统计,36(3):221-237.
7. 张乔微,李艳婷*（2020）基于LOF算法的多维混合型数据控制图设计[J].工业工程, 23(3):145-153.
8. 裴德昭,李艳婷*(2020)基于游程检验的多元非参控制图[J].工业工程,23(02):124-132.
9. 杨立宁,李艳婷*(2021)基于SVD和ARIMA的时空序列分解和预测.计算机工程:47(3),53-61.
10. 蒋文博,胡澜也,宋斐,樊林玉,李艳婷*(2021).基于比例风险模型与机器学习混合方法的电梯故障预测。工业工程与管理：19-27.
11. 胡澜也,蒋文博,李艳婷*.(2021) 基于LightGBM的风力发电机故障诊断，太阳能学报，42(11),255-259。
12. 叶祎旎，李艳婷*(2022) 基于CNN-集成学习的多风机故障诊断。工业工程，25(1),136-143。
13. 赵宇，李艳婷*. (2022) 面向小样本高维数据的秩检验非参控制图 . 中国机械工程，33(09),1104-1114。
14. 郝澜宇, 李艳婷*, 潘尔顺.(2022) 基于Copula模型的多维数据空间扫描监测方法. 统计与决策, 38(14), 5-9。
15. 郝澜宇，周笛，李艳婷*，潘尔顺（2022）考虑二元 Copula 统计量的晶圆制造叠加误差监测[J/OL]．中国机械工程.
16. 胡 洁,练朝春,李艳婷*，雷月霆,岳子桐(2022) 基于自然语言处理的车企客户反馈数据挖掘：上汽通用五菱公司的案例. 工业工程与管理，27（6）.
17. 彭星皓,李艳婷*.基于时空协方差函数的风能场景生成方法与应用[J] （2023）.350vip8888新葡的京集团学报,已录用。
18. 王鹏,李艳婷*,张宇. 基于在线Lasso VAR和EGARCH的风场功率集成概率预测[J] （2023）.350vip8888新葡的京集团学报, 已录用。
19. 赵宇 李艳婷 吴振宇 周笛 胡洁 (2023) 面向多模式多元未知分布的协方差过程监控, 中国机械工程，已录用。

专著：
《物联网大数据与产品全生命周期质量管理》，科学出版社, 2022，ISBN：9787030670281.