2015.09-2020.07 北京大学，工业工程与管理系，博士
2018.09-2019.11 威斯康星大学麦迪逊分校，工业与系统工程系，联合培养博士
2011.09-2015.06 南开大学，工业工程系，学士

2020.09至今 350vip8888新葡的京集团，助理教授、副教授

基于人工智能和统计学习的复杂工程系统分析，涉及时空统计、时空人工智能、小样本深度学习、工业大模型等前沿理论研究
• 时空动态系统的预测、监控、诊断与决策（轨道交通系统、城市物联网系统、储备粮质量管理系统等）
• 基于深度学习和多元传感数据融合的工业设备健康预测管理（PHM）

2025年入学的有直博、普博、硕博、专硕名额，指导本科生科研及竞赛，欢迎联系d.wang@sjtu.edu.cn

IEEE Transactions on Automation Science and Engineering, Associate editor
IEEE International Conference on Automation Science and Engineering, Associate editor
学术期刊会议评阅人：IEEE Transactions on Automation Science and Engineering，IISE Transactions，IEEE Transactions on Reliability，IEEE Transactions on Industrial Informatics，INFORMS Journal on Data Science, International Journal of Production Research，Journal of Intelligent Manufacturing，Computers and Industrial Engineering，Journal of Industrial and Production Engineering，IEEE International Conference on Automation Science and Engineering (CASE)，IEEE/SICE International Symposium on System Integration (SII)，工业工程与管理，等
学术会议组织活动
• 分会场主席，“Automation for Manufacturing and Logistics”, IEEE CASE, 2023
• 分会场主席，“Automation for Energy and Sustainability”, IEEE CASE, 2023
• 分会场组织者兼主席，“Data analytics for engineering and service system improvement”，INFORMS Annual Meeting，2019
• 分会场主席，“Process analytics and optimization for system and service improvement”，IEEE/SICE-SII，2017

国家自然科学基金委面上项目（72471145），考虑样本增益的城市多模态时空网络智能监控与诊断决策，主持，2025/01-2028/12
国家重点研发计划（2023YFB3307300），面向规模化生产过程的多源异构数据感知分析理论，任务负责人，2023/12-2026/11
国家重点研发计划（2022ZD0119305），全域多场景智能化码头关键技术与应用示范，课题五：码头数据算法共享的智能中枢，子课题负责人，2023/03-2026/02
教育部产学合作协同育人项目（SPC2821CHN23083010293289），融合端云协同的大数据分析课程建设，主持，2023/09-2025/01
上海市场监管局重点咨询项目，基于事前预防的产品质量安全治理模式创新研究，主持，2023/08-2023/11
上海市自然科学基金面上项目（22ZR1433000），基于时空人工智能的制造系统高维流数据建模与监控研究，主持，2022/04-2025/03
上海市晨光计划（21CGA12），交互事件网络系统的时空建模和状态监控，主持，2022/01-2024/12
国家自然科学基金青年项目（72101148），基于多元时空动态流数据的制造系统状态建模与过程监控研究，主持，2022/01-2024/12
上海市青年科技英才扬帆计划（21YF1420100），基于深度学习的复杂制造过程数据融合与异常诊断研究，主持，2021/04-2024/03
350vip8888新葡的京集团“双一流”建设项目（WF220502036），基于统计学习和人工智能对复杂工程系统的建模研究，主持，2020/09-2023/12
国家重点研发计划（2022YFB3402103），高端装备协同智能故障诊断理论与预测方法，课题三：高端装备退化评估与数模联动剩余寿命预测，参与，2022/12-2025/11
国家自然科学基金面上项目（72371161），线上线下联合服务模式下大型公立医院的服务策略与资源计划调度研究，参与，2024/01-2027/12
国家自然科学基金面上项目（52275499），变刚度局部薄壁零件多齿铣削加工过程的力学建模与加工误差控制方法，参与，2023/01-2026/12
国家自然科学基金重点项目（71932006），工业大数据环境下面向智能制造系统的质量科学管控方法研究，参与，2020/01-2024/12
国家自然科学基金面上项目（51875003），基于多源异构传感的增材制造过程监测与质量控制研究，参与，2019/01-2022/12
国家自然科学基金面上项目（71771004），基于多尺度数据融合的智能制造系统状态监测与故障诊断，参与，2018/01-2021/12
国家自然科学基金面上项目（71571003），基于自适应采样方法的高维流数据在线过程监测，参与，2016/01-2019/12
财政部国家公益科研专项（201413003），基于大数据的储藏数据采集、挖掘及云服务技术，参与，2014/10-2018/12

SCI期刊论文
34. Wang, Y., Li, F., Wang, D.*, and Qin, W. (2024) “A restricted-learning network with observation credibility inference for few-shot degradation modeling,” IEEE Transactions on Automation Science and Engineering, in press.
33. Wang, D., Xian, X., and Li, H. (2024) “Spatiotemporal interactive modeling of event-based dynamic networks,” Technometrics, in press.
32. Wang, Y., Wang, A., Wang, D.*, and Wang, D. (2024) “Deep learning-based sensor selection for failure mode recognition and prognostics under time-varying operating conditions,” IEEE Transactions on Automation Science and Engineering, in press.
31. Wang, D.*, Wang, A., and Song, C. (2024) “Flexible degradation modeling via the integration of local models and importance sampling,” IEEE Transactions on Instrumentation and Measurement, in press.
30. Wang, D., Xian, X., Li, H., and Wang, D. (2024) “Distribution-agnostic probabilistic few-shot learning for multimodal recognition and prediction,” IEEE Transactions on Automation Science and Engineering, in press.
29. Wang, D., Wang, Y., and Pan, E. (2024) “Multimodal recognition and prognostics based on features extracted via multisensor degradation modeling,” Journal of Quality Technology, in press.
28. Wang, D., Wang, Y., and Xian, X. (2024) “A latent variable-based multitask learning approach for degradation modeling of machines with dependency and heterogeneity,” IEEE Transactions on Instrumentation and Measurement, in press.
27. An, Y., Wang, D., Chen, L., and Zhang, X. (2023) “TCP-ARMA: A tensor-variate time series forecasting method,” IEEE Transactions on Automation Science and Engineering, in press, doi: 10.1109/TASE.2023.3322298.
26. Wang, D., Wang, Y., Xian, X., and Cheng, B. (2023) “An adaptation-aware interactive learning approach for multiple operational condition-based degradation modeling,” IEEE Transactions on Neural Networks and Learning Systems, in press, doi: 10.1109/TNNLS.2023.3305601.
25. Wang, D., Song, C., and Zhang, X. (2023) “Multimodal regression and mode recognition via an integrated deep neural network,” IISE Transactions, in press, doi: 10.1080/24725854.2023.2223245.
24. Wang, D.*, and Liu, K. (2023) “An integrated deep learning-based data fusion and degradation modeling method for improving prognostics,” IEEE Transactions on Automation Science and Engineering, in press, doi: 10.1109/TASE.2023.3242355.
23. Wang, D.*, Xian, X., and Song, C. (2023) “Joint learning of failure mode recognition and prognostics for degradation processes,” IEEE Transactions on Automation Science and Engineering, in press, doi: 10.1109/TASE.2023.3239004.
22. Zhao, C., Liu, F., Du, S., Wang, D., and Shao, Y. (2022) “An earth mover’s distance based multivariate generalized likelihood ratio control chart for effective monitoring of 3D point cloud surface,” Computers and Industrial Engineering, vol. 175, no. 2022, pp. 108911, 1–12.
21. Wang, D., Li, F., Liu, K., and Zhang, X. (2022) “Real-time IoT security solution leveraging an integrated learning-based approach,” ACM Transactions on Sensor Networks, in press, doi: 10.1145/3582009.
20. Zan, X., Wang, D., and Xian, X. (2023) “Spatial rank-based augmentation for nonparametric online monitoring and adaptive sampling of big data streams,” Technometrics, vol. 65, no. 2, pp. 243–256.
19. Yu, G., Wang, D., Liu, J., and Zhang, X. (2023) “Distribution-agnostic few-shot industrial fault diagnosis via adaptation-aware optimal feature transport,” IEEE Transactions on Industrial Informatics, vol. 19, no. 4, pp. 5623–5632.
18. Wang, D.*, Li, F., and Liu, K. (2023) “Modeling and monitoring of a multivariate spatio-temporal network system,” IISE Transactions, vol. 55, no. 4, pp. 331–347.
17. Wang, D., Liu, K., and Zhang, X. (2022) “A generic indirect deep learning approach for multisensor degradation modeling,” IEEE Transactions on Automation Science and Engineering, vol. 19, no. 3, pp. 1924–1940.
16. Wang, D., Liu, K., and Zhang, X. (2022) “A spatiotemporal prediction approach for a 3D thermal field from sensor networks,” Journal of Quality Technology, vol. 54, no. 2, pp. 215–235.
• 论文获得2019年INFORMS Annual Meeting数据挖掘分会最佳学生论文奖
• 论文获得2019年中国优选法统筹法与经济数学研究会工业工程分会年会优秀论文奖
15. An, Y., Wang, D., and Zhang, X. (2020) “A novel local temperature change detection approach in a 3D thermal field,” Quality Technology and Quantitative Management, vol. 17, no. 6, pp. 723–737.
14. Wang, D., Liu, K., Zhang, X., and Wang, H. (2020) “Spatiotemporal multitask learning for 3-D dynamic field Modeling,” IEEE Transactions on Automation Science and Engineering, vol. 17, no. 2, pp. 708–721.
• 论文获得2019年IISE Annual Conference数据分析和信息系统分会最佳学生论文提名奖
• 论文获得2018年中国质量与可靠性技术国际研讨会最佳展示二等奖
13. Wang, D., Liu, K., and Zhang, X. (2020) “Spatiotemporal thermal field modeling using partial differential equations with time-varying parameters,” IEEE Transactions on Automation Science and Engineering, vol. 17, no. 2, pp. 646–657.
12. Wang, D., Liu, K., and Zhang, X. (2019) “Modeling of a three-dimensional dynamic thermal field under grid-based sensor networks in grain storage,” IISE Transactions, vol. 51, no. 5, pp. 531–546.
• 论文获得2020年IISE Transactions最佳应用论文奖
• 论文入选2019年ISE Magazine专题文章
11. Wang, D., and Zhang, X. (2019) “Dynamic field monitoring based on multitask learning in sensor networks,” Sensors, vol. 19, no. 7, 1533, pp. 1–17.
10. Wang, D., and Zhang, X. (2019) “Modeling of a 3D temperature field by integrating a physics-specific model and spatiotemporal stochastic processes,” Applied Sciences, vol. 9, no. 10, 2108, pp. 1–13.

EI会议论文
9. Wang, Y., Li, F., and Wang, D.* (2024) “Few-shot RUL prediction with a Hypernetwork structure incorporating uncertainty quantification and calibration,” Proceedings of IEEE International Conference of Automation Science and Engineering, pp. 1–6.
8. Lin, J., Li, F., Wang, D., and Han, H. (2024) “Empowering industrial cybersecurity: dynamic temporal graph evolution with GNN edge updates,” Proceedings of Chinese Process Control Conference, pp. 1–6.
7. Li, H., Wang, L., Peng, Y., and Wang, D. (2023) “Kernel density estimation with efficient bandwidth selection,” Proceedings of the Winter Simulation Conference, pp. 1–12.
6. Yu, G. Xiao, L., Wang, Y., Wang, D., Liu, J., and Zhang, X. (2023) “UGG-DA: Uncertainty-guided gradual distribution adaptation and dynamic prediction with streaming data”, Proceedings of Chinese Control and Decision Conference, pp. 1–6.
5. Wang, Y. and Wang, D.* (2023) “An entropy- and attention-based feature extraction and selection network for multi-target coupling scenarios,” Proceedings of IEEE International Conference of Automation Science and Engineering, pp. 1–6.
4. Wang, X. and Wang, D.* (2023) “A control chart for monitoring multivariate spatiotemporal correlated data during grain storage,” Proceedings of IEEE International Conference of Automation Science and Engineering, pp. 1–6.
3. Wang, Y. and Wang, D.* (2022) “A data fusion-based LSTM network for degradation modeling under multiple operational conditions,” Proceedings of IEEE International Conference of Automation Science and Engineering, pp. 16–21.
2. Wang, D. and Zhang, X. (2017) “Modeling grain quality characteristics via dynamic models using sensing data,” Proceedings of the IEEE/SICE International Symposium on System Integration, pp. 336–341.
• 论文获得2017年IEEE/SICE-SII国际会议最佳论文奖
1. Wang, D., and Zhang, X. (2015) “A prediction method for interior temperature of grain storage via dynamics model: a simulation study,” Proceedings of IEEE International Conference of Automation Science and Engineering, pp. 1477–1483.

发明专利
1. 一种基于时空动态耦合的三维温度传感数据分析方法，第一发明人，专利号：ZL 201710188585.8, 2020
2. 一种基于迁移学习的仓储粮食温度场估计方法，第一发明人，专利号：ZL 201810042592.1, 2020
3. 基于时空条件动态建模的三维温度场监测方法，第二发明人，专利号：ZL 201910149975.3，2020
4. 基于多元时空数据融合的物联网系统建模和监控方法，第一发明人，专利号：ZL 202110166192.3，2021
5. 一种基于传感数据融合的温度场预测方法，第一发明人，专利号：ZL 201811066070.1，2023
6. 基于深度学习耦合建模的飞机发动机剩余寿命预测方法，第一发明人，专利号：ZL 202110556279.1，2023
7. 融合多任务学习的飞机发动机失效过程建模方法，第二发明人，专利申请号：202210334697.0
8. 基于联合学习的飞机发动机失效模式识别和剩余寿命预测方法，第一发明人，专利申请号：202210334726.3
9. 一种飞机发动机失效模式识别和寿命预测方法，第一发明人，专利申请号：202211123910.X
10. 一种多工况下飞机发动机剩余寿命预测方法，第二发明人，专利申请号：202211504814.X
11. 基于事件驱动的交通网络建模方法、事件预测方法及系统，第一发明人，专利申请号：202211569330.3
12. 基于传感数据退化建模的飞机发动机多失效模态预测方法，第二发明人，专利申请号：202310086813.6
13. 基于小样本学习的多失效模式下设备剩余寿命预测方法，第一发明人，专利申请号：202310277931.5

软件著作权
1. BRYAN LEE TENG，王迪，金鼎，毛子瑜，粮食仓储温度管理系统V1.0，登记号：2023SR0796911
2. 仓储粮食品质监测平台V1.0，登记号：2018SR229405，2018