Ph.D., Department of Industrial Engineering and Management, Peking University, 2015/09-2020/07
Joint Ph.D., Department of Industrial and Systems Engineering, University of Wisconsin-Madison, 2018/09-2019/11
B.S., Department of Industrial Engineering, Nankai University, 2011/09-2015/07

Associate Professor, Department of Industrial Engineering and Management, Shanghai Jiao Tong University, 2024/01-Present
Assistant Professor, Department of Industrial Engineering and Management, Shanghai Jiao Tong University, 2020/09-2023/12

Statistical Analysis and Artificial Intelligence for the Modeling and Monitoring of Complex Engineering Systems:
• Statistical Modeling, Prediction, and Monitoring of Spatiotemporal Dynamic Systems
• Deep Learning and Multisensory Data Fusion for Process Modeling, Prognostics, and Fault Diagnosis

1. National Science Foundation of China under Grant 72101148, PI, State modeling and process monitoring of manufacturing systems based on multivariate spatiotemporal dynamic flow data, 2022/01-2024/12.
2. Shanghai Sailing Program under Grant 21YF1420100, PI, Data fusion and abnormal diagnosis of complex manufacturing processes based on deep learning, 2022/01-2024/12.
3. National Science Foundation of Shanghai under Grant 22ZR1433000, PI, High-dimensional flow data modeling and monitoring of manufacturing systems based on spatiotemporal artificial intelligence, 2022/05-2025/04.
4. Shanghai Chenguang Program under Grant 21CGA12, PI, Spatiotemporal modeling and monitoring of interactive event network systems, 2022/01-2024/12.
5. Ministry of Education’s Industry-Education Cooperation Collaborative Education Project under Grant SPC2821CHN23083010293289, PI, Big data analytics course development via edge-cloud collaboration, 2023/09-2025/01.
6. Key Consultation Project of Shanghai Market Supervision Administration, PI, Innovative research on product quality and safety governance model based on precautionary prevention, 2023/08-2023/11.
7. “Double First Class” Construction Project of Shanghai Jiao Tong University under Grant WF220502036, PI, Statistical learning and artificial intelligence on modeling of complex engineering systems, 2021/09-2024/12.
8. National Key R&D Program of China Young Scientists Project under Grant 2023YFB3307300, Co-PI, Multi-source heterogeneous data perception and analysis theory for large-scale production processes, 2023/12-2026/11.
9. National Key R&D Program of China under Grant 2022ZD0119305, Co-PI, Key technologies and application demonstrations of intelligent port in all-domain and multi-scenario, 2023/03-2026/02.
10. National Key R&D Program of China under Grant 2022YFB3402100, Co-PI, A cooperative and intelligent fault diagnosis method for high-end equipment, 2022/12-2025/12.
11. National Science Foundation of China under Grant 72371161, Co-PI, Service strategy, resource planning and scheduling for public hospitals under the online and offline joint service mode, 2024/01-2027/12.
12. National Science Foundation of China under Grant 52275499, Co-PI, Mechanical modeling and processing error control of milling processes for local thin-wall parts with variable stiffness, 2023/01-2026/12.

1. 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, doi: 10.1109/TASE.2024.3372711.
2. 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, doi: 10.1080/00224065.2024.2315085.
3. 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, doi: 10.1109/TIM.2024.3374288.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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.
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. 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.
15. Wang, D., Liu, K., and Zhang, X.* (2022) “A spatiotemporal prediction approach for a 3D thermal field from sensor network,” Journal of Quality Technology, vol. 54, no. 2, pp. 215–235.
• This paper was selected as the Winner of Best Student Paper Award in Data Mining Section of INFORMS Annual Meeting, 2019.
• This paper was selected as the Outstanding Paper Award at the Annual Conference of the Industrial Engineering Branch of the Optimization and Coordination Law and Economic Mathematics Research Association, 2019, China.
16. 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. 723–731.
17. Wang, D., Liu, K., and Zhang, X.* (2020) “Spatiotemporal multitask learning for 3-D dynamic field modeling,” IEEE Transactions on Automation Science and Engineering, vol. 17, no. 2, pp. 708–721.
• This paper was selected as the Finalist of the Best Student Paper Award in DAIS Division of IISE Annual Conference, 2019.
• This paper was selected as Honorable Mention in the International Workshop on Reliability Technology and Quality Science, 2018, China.
18. 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.
19. 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.
• This paper was selected as the Winner of the Best Application Paper Award in IISE Transactions, 2020.
• This paper was selected as the Feature Article in ISE magazine, 2019.
20. Li, H., Wang, L., Peng, Y.*, and Wang, D. (2023) “Kernel density estimation with efficient bandwidth selection,” Proceedings of the Winter Simulation Conference, doi: 10.1109/WSC60868.2023.10407300, pp. 552–563.
21. 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, doi: 10.1109/CCDC58219.2023.10327028, pp. 5309–5314.
22. 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, doi: 10.1109/CASE56687.2023.10260339, pp. 1–6.
23. 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, doi: 10.1109/CASE56687.2023.10260366, pp. 1–6.
24. 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.
25. 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.
• This paper was selected as the Winner of the Best Paper Award in IEEE/SICE International Symposium on System Integration (SII), 2017.
26. 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.

Quality and Reliability Engineering, Postgraduate course, 2021, 2022, 2023, 2024
Big Data Analysis, Undergraduate course, 2021, 2022, 2023
Undergraduate Full Advisor, 2020, 2021, 2022, 2023
Advisor of Undergraduate Graduation Projects, 2021, 2022, 2023
Advisor of Undergraduate “Participation in Research Program” (PRP), 2022, 2024
Advisor of Undergraduate/Postgraduate Science and Technology Innovation Competitions, 2022, 2023

Patents
1. Wang, D., “A remaining life prediction method aircraft engines based on deep learning coupled modeling,” Chinese invention patent, ZL 202110556279.1, 2023.
2. Wang, D., and Zhang, X., “A thermal field prediction method based on sensor data fusion,” Chinese invention patent, ZL 201811066070.1, 2023.
3. Wang, D., Cheng, B., and An, Y., “A modeling and monitoring method for IoT systems based on multivariate spatiotemporal data fusion,” Chinese invention patent, ZL 202110166192.3, 2021.
4. An, Y., Wang, D., Zhang, X., and Lan, X. “A three-dimensional temperature field monitoring method based on spatiotemporal dynamic modeling,” Chinese invention patent, ZL 201910149975.3, 2020.
5. Wang, D., and Zhang, X., “A three-dimensional temperature sensor data analysis method based on spatiotemporal dynamic modeling,” Chinese invention patent, ZL 201710188585.8, 2020.
6. Wang, D., and Zhang, X., “A transfer learning method for estimating grain temperature field during storage,” Chinese invention patent, ZL 201810042592.1, 2020.

Software Copyrights
1. Teng, B. L., Wang, D., Jin, D. and Mao, Z., “Grain storage thermal management system”, Chinese software copyright, CN Software NO. 2023SR0796911, 2023.
2. Wang, D., and Zhang, X., “Platform of grain quality monitoring during storage”, Chinese software copyright, CN Software NO. 2018SR229405, 2018.

Editorial Board
Associate editor, IEEE International Conference on Automation Science and Engineering (CASE), 2024-Present

Academic Paper Referees
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), Winter Simulation Conference (WSC)

Memberships
IEEE, INFORMS, IISE

Conference Organizing Activities
1. Chair, session on “Automation for Manufacturing and Logistics”, IEEE International Conference on Automation Science and Engineering (CASE), 2023.
2. Chair, session on “Automation for Energy and Sustainability”, IEEE International Conference on Automation Science and Engineering (CASE), 2023.
3. Organizer and chair, session on “Data analytics for engineering and service system improvement”, INFORMS Annual Meeting, 2019.
4. Chair, session on “Process analytics and optimization for system and service improvement”, IEEE/SICE International Symposium on System Integration (SII), 2017.

• “Excellent” in the Annual Performance Evaluation of Shanghai Jiao Tong University, 2023.
• Outstanding Class Advisor at Shanghai Jiao Tong University, 2023.
• First Prize in Teaching Achievement at Shanghai Jiao Tong University, 2023.
• Outstanding Doctoral Dissertation from the Management Science and Engineering Society of China, 2022.
• First-Class Undergraduate Course at Shanghai Jiao Tong University, “Quality and Maintenance Management”, 2021.
• Shanghai Chenguang Program, 2021.
• Shanghai Sailing Program, 2021.
• Outstanding Graduate Award in Beijing, Beijing Municipal Education Commission, 2020.
• Winner of the Best Application Paper Award in IISE Transactions, 2020.
• Winner of the Best Paper Award in Data Mining Section of INFORMS Annual Meeting, 2019.
• Finalist of the Best Student Paper Award in DAIS Division of IISE Annual Conference, 2019.
• Feature Article of ISE Magazine, 2019.
• Outstanding Paper Award at the Annual Conference of the Industrial Engineering Branch of the Optimization and Coordination Law and Economic Mathematics Research Association, China, 2019
• Honorable Mention in International Workshop on Reliability Technology and Quality Science, China, 2018.
• First Prize in National College Innovation Competition of Industrial Engineering and Lean Management, China, 2018.
• Winner of the Best Paper Award in IEEE/SICE International Symposium on System Integration (SII), 2017.
• National Scholarship, Ministry of Education of China, 2014, 2018, 2019.

Advisor
• Outstanding Paper Award at the National Industrial Engineering Doctoral Student Academic Forum of China (Student: Ying Wang), 2023.
• First Prize in the National Excellent Course Design Competition for Industrial Engineering (Students: Hongyang Song, Renquan Liu, Mingye Mo, Wenqing Ma, Yichen Hou), 2023.
• First Prize in the Industrial Engineering and Lean Management Innovation Competition at the China College Students’ Mechanical Engineering Innovation and Creativity Contest (Students: Yuhui Wang, Ying Wang, Peihan Zhang), 2022.
• First Prize in the Shanghai Engineering Management Innovation Competition (Students: Yuhui Wang, Ying Wang), 2022.
• Meritorious Winner in the Mathematical Contest in Modeling (Students: Yizhuo Cai, Yeyue Cai, Yuan Meng), 2022.
• Honorable Mention in the Mathematical Contest in Modeling (Students: Haoruo Liu, Shifan Liu, Jingyi Wang), 2023.
• Honorable Mention in the Mathematical Contest in Modeling (Students: Wei Xu, Kaitong Cui, Runjin Yu), 2022.
• Second Prize in the National Excellent Course Design Competition for Industrial Engineering (Students: Ding Jin, Yuanyuan Li, Ruichen Zhu, Qiuge Wang, Erya Guo), 2022.
• Third Prize in the National Graduate Mathematical Modeling Competition (Students: Ying Wang, Xinyu Pan, Peihan Zhang), 2023.
• Third Prize in the National Graduate Engineering Management Case Competition (Students: Ying Wang, Yuhui Wang, Peihan Zhang, Xingyu Wang, Xinyu Pan), 2023.
• Third Prize in the National Industrial Engineering Application Case Competition (Students: Ding Jin, Teng Li, Ziyu Mao), 2023.
• Third Prize in the Industrial Engineering and Lean Management Innovation Competition at the China College Students’ Mechanical Engineering Innovation and Creativity Contest (Students: Ding Jin, Teng Li, Ziyu Mao), 2023.
• Third Prize in the National Graduate Mathematical Modeling Competition (Students: Yuhui Wang, Xingyu Wang, Ying Wang), 2022.