2004-2008    香港科技大學 工業(yè)工程與工程管理專業(yè)   博士
2001-2004    南開大學 概率論與數(shù)理統(tǒng)計專業(yè)    碩士
1997-2001    南開大學 概率論與數(shù)理統(tǒng)計專業(yè)    學士

2008-至今 上海交通大學機械與動力工程學院工業(yè)工程與物流管理系

1）復雜裝備機理+數(shù)據(jù)驅動的智能預測、過程優(yōu)化與監(jiān)控、異常檢測、故障診斷
2）多元時空數(shù)據(jù)的預測與建模
3）高維復雜數(shù)據(jù)的統(tǒng)計過程控制方法
研究結合汽車發(fā)動機、電子、新能源裝備等制造業(yè)領域開展工程應用。

2026年入學碩士研究生名額1名。基地碩士研究生名額1名。

2026年入學博士研究生名額1名。

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. 上海市質量金獎、市長獎、上海市重點產品質量攻關獎評審專家（2015-）

3. 上海市經(jīng)濟和信息化委員會”質量標桿”專家（2017-）

4. 上海市質量技術應用統(tǒng)計學會理事（2017-）
   

5. 上海市質量協(xié)會質量技術獎項目評審專家（2018-）

6. 江蘇省市場監(jiān)督管理局“江蘇省質量專家”（2019-2023）
   
   

   
   

1. 國家自然科學基金青年項目“多工序制造過程中離散型和混合型質量數(shù)據(jù)的統(tǒng)計過程監(jiān)控方法研究”(70902070)。負責人。2010-2012。

2. 國家自然科學基金面上項目“多元計數(shù)數(shù)據(jù)的統(tǒng)計過程控制方法研究”(71272003)，負責人。2013-2016。

3. 國家自然科學基金面上項目“多元復雜時空數(shù)據(jù)建模與監(jiān)控方法研究”(71672109)，負責人。2017-2020。
   

4. 國家自然科學基金面上項目“復雜數(shù)據(jù)環(huán)境下大規(guī)模風力發(fā)電場的功率預測、狀態(tài)監(jiān)控和故障診斷”(72072114)，負責人。2021-2024。

5. 國家自然科學基金面上項目“多源大數(shù)據(jù)驅動的多風電場協(xié)同功率預測和運行監(jiān)測研究”(72471139). 負責人。2025-2028。

6. 國家重點研發(fā)計劃項目，鋼鐵全流程多工序動態(tài)協(xié)同運行優(yōu)化技術及示范應用，子課題負責人。 2020-2023。
   

7. 國家自然科學基金面上項目“質量管理中高維數(shù)據(jù)的統(tǒng)計過程控制研究”  (71172131)，研究骨干。2012-2015。
   

8. 國家自然科學基金重點項目“基于物聯(lián)網(wǎng)的產品狀態(tài)智能監(jiān)控與質量管理”(71531010)，研究骨干。2016-2020。

9. 上海交通大學晨星學者獎勵計劃B類。負責人。2014-2016.

10. 面向冷軋薄板大數(shù)據(jù)的統(tǒng)計過程控制軟件包開發(fā)，寶山鋼鐵股份有限公司。2021-2022，負責人.

11. 風電機組智能化運維關鍵技術開發(fā)，2024-2025，負責人。

12. 基于深度學習的故障預測與飛行安全風險分析研究，2025-2026，負責人。

13. 融合工程知識與數(shù)據(jù)的裝配過程質量改進關鍵技術研究，2025-2026，負責人。

部分代表性論文：

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).

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).

3.  Han, D, Tsung, F. and Li, Y. (2010) “A Nonlinear Filter Control Chart For Detecting Dynamic Changes”. Statistica Sinica, 20, 1077-1096. (SCI).

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 Applid Statistics, 37(7), 1089-1111. (SCI).

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).

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)

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, 52, 2, 445-461.(SCI)

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. 66, 78-89. (SCI)

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)

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 ,  180, 392–401.(SCI)

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. 66:78–89. 

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 . 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 .  213, 15，118371 .

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 .  149, 106839。

18. Li, Y. Wu, Z. (2020) A condition monitoring approach of multi-turbine based on VAR model at farm level. Renewable Engergy , 166, 66-80. (SCI)

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, 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 Yanting* (2021) 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, 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, 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, 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, 198, 155-168

26. Peng Wang, Yanting Li*（2023） Probabilistic power curve estimation based on meteorological factors and density LSTM. Energy，269(15), 126768. https://doi.org/10.1016/j.energy.2023.126768

27.  Zhenyu Wu, Li, Yanting*, 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.

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. 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. https://doi.org/10.1016/j.aei.2023.102031

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.

31. Yanting Li, Zhenyu Wu*, Yan Su (2023) Adaptive short-term wind power forecasting with concept drifts. Renewable Energy, 217,119146.  https://doi.org/10.1016/j.renene.2023.119146

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. https://doi.org/10.1016/j.measurement.2024.114325

33.  Zhenyu Wu, Yanting Li*(2024) The Condition Monitoring Scheme for Industrial IoT Scenario: A Distributed Modeling for High-dimensional Nonstationary Data. Computers & Industrial Engineering. 197, November 2024, 110545  https://doi.org/10.1016/j.cie.2024.110545

34.  Yanting Li, Peng Wang, Zhenyu Wu*, Yan Su.  (2024) Collaborative Monitoring of Wind Turbine Performance based on Probabilistic Power Curve Comparison. Renewable Energy. 231, 120919. https://doi.org/10.1016/j.renene.2024.120919

35. Yizhuo Cai, Yanting Li* (2024) Short-term wind speed forecast based on dynamic spatio-temporal directed graph attention network. Applied Energy, 375, 124124. https://doi.org/10.1016/j.apenergy.2024.124124

36. Xinghao Peng, Yanting LI* (2024) A Graph Attention Network with Spatio-Temporal Wind Propagation Graph for Wind Power Ramp Events Prediction. Volume 236,  121280. https://doi.org/10.1016/j.renene.2024.121280

37. Li, Yanting*; Zhao, Yu; Yue, Zitong. (2024) Covariance monitoring of multi-mode multivariate IoT devices data.https://doi.org/10.1080/03610918.2024.2438166.

38. Rui Zhou, Yanting Li*, Xinhua Lin (2025) A clustered federated learning framework for collaborative fault diagnosis of wind turbines[J]. Applied Energy,377: 124532. https://doi.org/10.1016/j.apenergy.2024.124532

39. Rui Zhou, Yanting Li*(2025) FedCOP: Federated Contrastive Orthonormal Prototype Learning Framework for Multi-Wind Farm Collaborative Fault Detection[C].2025 IEEE 21st International Conference on Automation Science and Engineering. (EI) 

40. Wu, Z. Y., Yanting Li*, Chen, N., Wang, Z. J., & Mu, C. X. (2025). Multiple Change Point Detection Method of Profile Data With False Discovery Rate Control. IEEE Transactions on Knowledge and Data Engineering, 37(9), 5481-5494. https://doi.org/10.1109/TKDE.2025.3584034 

41. Wang, D., Pan, X. Y., Pan, E. S., & Yanting Li* (2025). An Adversarial Branched Network for Degradation Modeling Under Multiple Failure Modes. IEEE Transactions on Automation Science and Engineering, 22, 13501-13518. https://doi.org/10.1109/TASE.2025.3549061 

42. Yang, X. L., & Yanting Li* (2025). Using Heterogeneous Extractor to Transfer Local-Global Knowledge for Cross-Domain Rolling Bearing Fault Diagnosis. IEEE Transactions on Instrumentation and Measurement, 74, 3546612. https://doi.org/10.1109/TIM.2025.3582302 

43. Wang, Z. J., Yanting Li*, Zhang, Z. J., & Pan, E. S. (2025). Privacy-Preserving Distributed Fault Diagnosis for Multiple Wind Farms Using a Federated Feature Fusion Method. IEEE Transactions on Automation Science and Engineering, 22, 21525-21540. https://doi.org/10.1109/TASE.2025.3613954 

44. Zhou, R. Y., Shu, L. J., Huang, W. P., & Yanting Li* (2025). A new adaptive EWMA control chart based on Catoni’s function for monitoring process variability. Journal of Quality Technology. https://doi.org/10.1080/00224065.2025.2523002 

45. Yun Liu, Lianjie Shu, Guoliang Tian, Yanting Li* (2025) A Comparison of Robust Principal Component Analysis in High dimensions. Communications in Statistics - Simulation and Computation. https://doi.org/10.1080/03610918.2025.2461583 

46. Yan Su, Yanting Li,Electrochemical transport in topology optimized electrodes during cyclic charge–discharge processes,Journal of Energy Storage, Volume 141, Part D, 2026, 119433, ISSN 2352-152X, https://doi.org/10.1016/j.est.2025.119433.

47. Cai Y, Yanting Li*. Probabilistic Prediction for Multi-Equipment Systems Based on Bayesian Spatio-Temporal Graph Attention Network[C]//2025 16th International Conference on Reliability, Maintainability and Safety (ICRMS). IEEE, 2025. （EI）

48. Wang, Z.,  Li*  Y.,  Ye Z., Wu, Z. and Zhou R. (2026) Federated Incremental Collaborative Fault Diagnosis Method for Dynamic Data Streams in Multi-Wind Farms, IEEE Transactions on Cybernetics. 10.1109/TCYB.2025.3646266

1.  何勇,李艷婷*（2017）基于向量自回歸模型的移動通信基站流量預測[J].工業(yè)工程與管理,22(04)，79-84.

2.  婁璐，李艷婷*（2018）面向未知自相關過程的Bootstrap控制圖設計，《工業(yè)工程》，21(4), 23-33.

3.  劉姝君,李艷婷*（2019）基于深度高斯過程的多元類別數(shù)據(jù)分布估計[J].計算機工程,45(2):160-166.

4.  龍威,李艷婷*（2019）基于多元泊松時間序列的累積和控制圖設計[J].工業(yè)工程與管理,24(4):105-112.

5.  張喬威，李艷婷*（2019）基于R-Vine Copula的多維混合型數(shù)據(jù)控制圖設計.工業(yè)工程，22（5）126-149。

6.  龍威,李艷婷*（2020）基于多元泊松模型的累積和控制圖設計[J].應用概率統(tǒng)計,36(3):221-237.

7.  張喬微,李艷婷*（2020）基于LOF算法的多維混合型數(shù)據(jù)控制圖設計[J].工業(yè)工程, 23(3):145-153.

8.  裴德昭,李艷婷*(2020)基于游程檢驗的多元非參控制圖[J].工業(yè)工程,23(02):124-132.

9.  楊立寧,李艷婷*(2021)基于SVD和ARIMA的時空序列分解和預測.計算機工程:47(3),53-61.

10.  蔣文博,胡瀾也,宋斐,樊林玉,李艷婷*(2021).基于比例風險模型與機器學習混合方法的電梯故障預測。工業(yè)工程與管理：19-27.

11.  胡瀾也,蔣文博,李艷婷*.(2021) 基于LightGBM的風力發(fā)電機故障診斷，太陽能學報，42(11),255-259。

12. 葉祎旎，李艷婷*(2022) 基于CNN-集成學習的多風機故障診斷。工業(yè)工程，25(1),136-143。

13. 趙宇，李艷婷*. (2022) 面向小樣本高維數(shù)據(jù)的秩檢驗非參控制圖 . 中國機械工程，33(09),1104-1114。

14. 郝瀾宇, 李艷婷*, 潘爾順.(2022) 基于Copula模型的多維數(shù)據(jù)空間掃描監(jiān)測方法. 統(tǒng)計與決策, 38(14), 5-9。

15. 郝瀾宇，周笛，李艷婷*，潘爾順（2022）考慮二元 Copula 統(tǒng)計量的晶圓制造疊加誤差監(jiān)測[J/OL]．中國機械工程.

16. 胡 潔,練朝春,李艷婷*，雷月霆,岳子桐(2022) 基于自然語言處理的車企客戶反饋數(shù)據(jù)挖掘：上汽通用五菱公司的案例. 工業(yè)工程與管理，27（6）.

17. 彭星皓,李艷婷*.（2023）基于時空協(xié)方差函數(shù)的風能場景生成方法與應用[J] .上海交通大學學報,已錄用。

18. 王鵬,李艷婷*,張宇. （2023）基于在線Lasso VAR和EGARCH的風場功率集成概率預測[J] .上海交通大學學報, 57（7）, 845-858.

19. 趙宇 李艷婷 吳振宇 周笛 胡潔 (2023) 面向多模式多元未知分布的協(xié)方差過程監(jiān)控, 中國機械工程，已錄用。

20. 岳子桐,李艷婷,趙宇.基于神經(jīng)網(wǎng)絡和穩(wěn)健估計的風電機組狀態(tài)監(jiān)測[J].中國機械工程,2025,36(08):1842-1852.

21. 黃亞欣,李艷婷.基于雙域卷積Transformer的滾動軸承剩余壽命預測[J].機床與液壓,2025,53(20):1-7.

22. 李艷婷,王迪.人工智能和大數(shù)據(jù)驅動的質量管理[J].上海質量,2025,(07):12-16.

專著：

《物聯(lián)網(wǎng)大數(shù)據(jù)與產品全生命周期質量管理》，科學出版社, 2022，ISBN：9787030670281.

《質量管理學》，上海交通大學出版社，2025，9787313320445 。