张晨，清华大学工业工程系副教授。2012年于天津大学获得电子科学与技术(光电子方向)学士学位。2017年于新加坡国立大学获得工业系统工程管理博士学位。研究方向包括基于统计学方法和人工智能方法的大规模复杂系统建模、根因分析、在线监控、异常检测、 自适应数据采集，以及分布式计算策略。

更多信息请访问主页：https://thuie-isda.github.io/

张晨老师每年都有计划招收博士、硕士、科研助理、博士后， 欢迎具有良好数学基础，擅长编程，对数据科学相关研究感兴趣的同学发送简历到 zhangchen01@tsinghua.edu.cn

2013— 2017 新加坡国立大学 工业系统工程管理 博士

2008—2012 天津大学 电子科学与技术 学士

2020—至今 : 清华大学工业工程系 副教授

2018—2020 : 清华大学工业工程系 助理教授

2017—2018: 新加坡管理大学 信息系统学院 博士后

•本科生：

实验设计

机器学习与大数据

工程经济学

•研究生：

高级统计学

高等质量管理

工程统计分析

数据可视化

国家自然科学基金面上项目: 基于函数型数据建模与异常检测的多阶段制造原位过程监控，2023.01-2026.12，主持

北京市自然科学基金面上项目:面向工业物联网的网络流数据统计建模与在线监控，2022.01-2024.12，主持

国家自然科学基金青年项目: 基于复杂轮廓数据的统计建模和在线监控研究，2020.01-2022.12，主持

国家自然科学基金重点项目: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，2020.01-2024.12，参与

期刊

1. An, X., Chua, J., Wang, Y., Hemelings, R., Husain R., Chong R., Wong T., Aung T., Wong D.*, Zhang, C.*, Schmetterer L.*, Addressing Glaucoma Structure-Function Relationship: A Multi-Task Learning Framework with Multi-Modal and Unpaired Data, IEEE Transactions on Medical Imaging, conditionally accepted.

2. Liu, P., Zhang, C.* (2025), Stream of Variation Modeling and Monitoring for Heterogeneous Profiles in Multi-Stage Manufacturing Processes, IISE Transactions, 1-14, https://doi.org/10.1080/24725854.2024.2413122.

3. Guo, J., Han, C., and Zhang, C.* (2025), MT-RAM: MultiTask-Recurrent Attention Model for Partially Observable Image Anomaly Classification and Localization, IISE Transactions, 1-16, https://doi.org/10.1080/24725854.2024.2425292.

4. Ma, Y., Xia, X., Guo, J., and Zhang, C.* (2025), A Deep Reinforcement Learning Method Solving Bilevel Optimization for Product Design Considering Remanufacturing, IEEE Transaction on Engineering Management, 72, 573-590.

5. Yang, X, Lan, T., Qiu, H., Zhang, C.* (2025), Nonlinear Causal Discovery via Dynamic Latent Variables, IEEE Transactions on Automation Science and Engineering, 22, 10381-10391.

6. Yang, X., Niu, B., Lan, T., Zhang, C.* (2025), Federated Multi-task Bayesian Network Learning in the Presence of Overlapping and Distinct Variables, IISE Transactions, 57(7), 773–787.

7. Tian, X., Zhang, C.*, Zheng, B. (2024), Fine-Grained Passenger Load Prediction inside Metro Network via Smart Card Data, International Journal of Intelligent Systems, 2024(1), 6643018.

8. Ma, Y., Zhang, C.*, Du, G. (2024), Reverse logistics platform decisions integrating crowdsourced contracting: A three-level interactive optimization approach for product design considering remanufacturing, Computers & Industrial Engineering, 193, 110305.

9. Liu, P., Lin, J., Zhang, C.* (2024), Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach, IEEE Transactions on Knowledge and Data Engineering, 36(12), 8421-8433.

10. Lin, J., Lan, T., Zhang, B., Deng, K., Miao, D., Ye., J., Li, Y., and Zhang, C.* (2024), Multi-Scenario Cellular KPI Prediction Based on Spatiotemporal Graph Neural Network, IEEE Transactions on Automation Science and Engineering, 22, 5131-5142.

11. Liu, P., Xu, H., and Zhang, C.* (2024), A Comprehensive Survey of Recent Research on Profile Data Analysis, Journal of Quality Technology, 56(5), 428–454.

12. An, X., Zhang, C.*, Hou, L., and Wang, K. (2024), Coupled Epidemic-Information Propagation with Stranding Mechanism on Multiplex Metapopulation Networks, IEEE Transactions on Computational Social Systems, 11(5), 6727-6744.

13. Sergin, N., Hu, J., Li, Z., Zhang, C., and Yan, H.^#* (2024), Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling, INFORMS Journal on Data Science, 4(1), 33-50.

14. Li, W., and Zhang, C.* (2023), A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality, IISE Transactions, 55(11), 1118–1132.

15. Yang, X., Zhang, C.*, and Cao, H.^# (2023), A Cluster-oriented Bayesian Network Approach for Mixed-type Event Prediction with Application in Order Logistics, IEEE Transactions on Industrial Informatics, 19(10), 10069 - 10078.

16. Yang, X., and Zhang, C.* (2023), Online Directed Structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach, IISE Transactions, 56(5), 527–540.

17. Guo, J., Yan, H., and Zhang, C.* (2023), Thompson Sampling based Partially Observable Online Change Detection for Exponential Families, INFORMS Journal on Data Science, 3(2), 145-161.

18. An, X., Li, P., and Zhang, C.* (2023), Deep Cascade-Learning Model via Recurrent Attention for Immunofixation Electrophoresis Image Analysis, IEEE Transactions on Medical Imaging, 42(12), 3847-3859.

19. Meng, H., Li, Y. F.*, and Zhang, C. (2022), Estimation of discharge voltage for lithium- ion batteries through orthogonal experiments at subzero environment, Journal of Energy Storage, 52(C), 10508.

20. Guo, J., Yan, H., and Zhang, C.* (2022), A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling, Technometrics, 65(2), 179-191.

21. Li, Z., Yan, H., Zhang, C., and Tsung, F.* (2022), Individualized Passenger Travel Pattern Multi-Clustering based on Graph Regularized Tensor Latent Dirichlet Allocation, Data Mining and Knowledge Discovery, 36(4), 1247-1278.

22. Yang, X., Zhang, C.*, and Zheng, B. H. (2022), Segment-Wise Time-Varying Dynamic Bayesian Network with Graph Regularization, ACM Transactions on Knowledge Discovery from Data, 16(6), 1-23.

23. Zhou, P., Liu, P., Wang, S., Zhang, C.*, Zhang, J., and Li, S.(2022), Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing, Journal of Manufacturing Systems, 64, 356-371.

24. Li, W., and Zhang, C.* (2022), A Hidden Markov Model for Condition Monitoring of Time Series Data in Complex Network Systems, IEEE Transactions on Reliability, 72(4), 1478-1492.

25. Zhang, C.*, Zheng, B. and Tsung, F. (2022), Multi-view Metro Station Clustering based on Passenger Flows: A Functional Data Edged Network Community Detection Approach, Data Mining and Knowledge Discovery, 37(3), 1154-1208.

26. Liu, P., Du, J., Zang, Y., Zhang, C.*, and Wang, K. (2022), In-profile Monitoring for Cluster-Correlated Data in Advanced Manufacturing System, Journal of Quality Technology, 55(2), 195–219.

27. Wu, H., Zhang, C., and Li, Y F. (2021), Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model, Technometrics, 64(2), 210-223.

28. Zhang, C., Yan, H.*, Lee, S., and Shi, J.(2021), Dynamic Multivariate Functional data Modeling via Sparse Subspace Learning, Technometrics , 63(3), 370-383.

29. Zhang, C.*, Hoi, C.H. and Tsung, F. (2020), Multivariate Functional Data Modeling via Nonnegative Functional Factorization with Time Warping, ACM Transactions on Knowledge Discovery from Data, 14(6), 1-23.

30. Zhang, C.* and Hoi, C.H. (2020), A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment, IEEE Transactions on Automation Science and Engineering, 19(1), 441-456.

31. Li, Z., Yan, H., Zhang, C., and Tsung, F.* (2020), Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile, IEEE Robotics and Automation Letters, 5(4), 5010-5017.

32. Zhang, C., Chen, N. and Wu, J. * (2019), Spatial Rank based High-dimensional Monitoring Through Random Projection, Journal of Quality Technology, 52 (2), 111-127.

33. Wu, J., Xu, H., Zhang, C., and Yuan, Y. (2019), A Sequential Bayesian Partitioning Approach for Online Steady-State Detection of Multivariate Systems, IEEE Transactions on Automation Science and Engineering, 16(4), 1882-1895.

34. Xian, X., Zhang, C., Bonk, S., and Liu, K. (2019), Online Monitoring of Big Data Streams: A Rank-based Sampling Algorithm by Data Augmentation, Journal of Quality Technology, 53 (2), 135-153.

35. Zhang, C., Yan, H., Lee, S., and Shi, J.* (2018), Multiple Profiles Sensor-Based Monitoring and Anomaly Detection, Journal of Quality Technology, 50(4), 344-362.

36. Zhang, C., Yan, H.*, Lee, S., and Shi, J.(2018), Multichannel Profile Monitoring based on Sparse Multichannel Functional Principal Component Analysis, IISE Transactions, 50(10), 878-891.

37. Zhang, C., and Chen, N.* (2018), Statistical Analysis of Simulation Outputs from Parallel Computing, ACM Transactions on Modeling and Computer Simulation (TOMACS), 28(3), 21-35.

38. Zhang, C., Lei, Y., Zhang, L., and Chen, N.* (2017), Modelling Tunnel Profile in the Presence of Coordinate Errors: A Gaussian Process-Based Approach, IISE Transactions, 49(11), pp.1065-1077.

39. Zhang, C., Chen, N.*, and Li, Z. (2017), State space modeling of autocorrelated multivariate Poisson counts, IISE Transactions, 49(5), 518-531.

40. Zhang, C., Chen, N.*, and Zou, C. (2016), Robust multivariate control chart based on goodness-of-fit test, Journal of Quality Technology, 48(2), 139-161.

会议

41. Lan, T., Li, Z., Li, Z., Bai, L., Li, M., Tsung, F., Ketter, W., Zhao, R., and Zhang, C.* (2023), MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 1188-1199.

42. Zhang, W., Zhang, C.*, and Tsung, F. (2022), GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning, 31st International Joint Conference on Artificial Intelligence (IJCAI), 2390-2397.

43. Zhang, W., Zhang, C., and Tsung, F. (2021), Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting, IEEE 17th International Conference on Automation Science and Engineering (CASE), 1515-1520.

44. He, B., Li,S., Zhang, C.*, Zheng, B., and Tsung, F. (2021), Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach, Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PCDD), 321-336.

45. Li, Z., Yan, H., Zhang, C. and Tsung, F. (2020), Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction, 34^th AAAI Conference on Artificial Intelligence, 4804-4810.

46. Zhang, C., and Hoi, C.H.* (2019), Online Learning for Partially Observable Multisensor Sequential Change Detection, 33^rd AAAI Conference on Artificial Intelligence, 5733-5740.

书籍章节

47. Liu, P., Zhang, C.*, Advanced Data Analytical Techniques for Profile Monitoring. in Multimodal and Tensor Data Analytics for Industrial Systems Improvement (pp. 21-39). Cham: Springer International Publishing.

48. Zhang, C., Wang, K., Tsung, F., Big Data, in International Encyclopedia of Statistical Science, 2nd Edition, Ed. Lovric, M., Springer, New York, May, 2025.

49. Zhang, C., Li, Y., Tsung, F., Industrial Big Data, in International Encyclopedia of Statistical Science, 2nd Edition, Ed. Lovric, M., Springer, New York, May, 2025.