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：
机器学习与大数据
工程经济学
•研究生：
高等质量管理
工程统计分析

系统信息学：工业大数据建模（半导体制造，航空航天制造，钢铁冶金）, 质量管理, 统计过程监控

智慧交通：城市轨道交通数据挖掘，交通拥堵根因分析

智能医学：个性化医疗， 基于人工智能的医学影像分析

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

25. Yang, X., and Zhang, C .* (2023) Online Directed Structural Change-point Detection: A Segment-wise Time-varying Dynamic Bayesian Network Approach, IISE Transactions, accepted.
24. 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, accepted.

23. Li, W., and Zhang, C .* (2022) A Markov-Switching Hidden Heterogeneous Network Autoregressive Model for Multivariate Time Series Data with Multimodality, IISE Transactions, online.

22. Liu, P., Du, J., Zang, Y., Zhang, C .*, and Wang, K. (2022) Functional state-space model for multi-channel autoregressive profiles with application in advanced manufacturing, Journal of Quality Technology, online.

21. 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, online.

20. 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, online.

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

18. Yang, X., Zhang, C .*, and Zheng, B. H. (2022) Structure Learning for Time-varying Dynamic Bayesian Network with Fused lasso and Graph Laplacian. ACM Transactions on Knowledge Discovery from Data, 16, (6), 1-23.

17. 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, pages1247–1278.

16. Guo, J., Yan, H., and Zhang, C .* (2022) A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling, Technometrics, online https://doi.org/10.1080/00401706.2022.2127914.

15. 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.

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

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

12. Zhang, C . and Hoi, C.H. (2020) A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment, accepted, IEEE Transactions on Automation, Systems and Engineering .

11. Zhang, C ., Hoi, C.H. and Tsung, F. (2020). Multivariate Functional Data Modeling via Nonnegative Functional Factorization with Time Warping, accepted, ACM Transactions on Knowledge Discovery from Data .

10. Xian, X., Zhang, C ., Bonk, S., and Liu, K. (2019). Online Monitoring of Big Data Streams: A Rank-based Sampling Algorithm by Data Augmentation," in press, Journal of Quality Technology .

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

8. Zhang, C ., Chen, N. and Wu, J. (2019). Spatial Rank based High-dimensional Monitoring Through Random Projection, accepted, Journal of Quality Technology .

7. Zhang, C ., Yan, H., Lee, S., and Shi, J. (2020). Dynamic Multivariate Functional data Modeling via Sparse Subspace Learning, accepted, Technometrics ( 2017 INFORMS Data Mining Section Best Paper Award ).

6. 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.

5. 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(2016 INFORMS Quality, Statistics, and Reliability Section Best Student Poster Award).

4. Zhang, C ., Yan, H., Lee, S., and Shi, J. (2017). Multiple Profiles Sensor-Based Monitoring and Anomaly Detection, accepted, Journal of Quality Technology , 50:4, 344-362.

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

2. Zhang, C ., Chen, N., and Li, Z. (2016). State Space Modeling of Autocorrelated Multivariate Poisson Counts, IISE Transactions, 49(5), 518-531.

1. 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.

11. Lan, T., Ziyue Li, Zhishuai Li, Lei Bai, Man Li, Fugee Tsung, Wolfgang Ketter, Rui Zhao, and Chen Zhang *, “MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis”, SIGKDD, 2023, accepted.

10. 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), 2022.

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

8. He, B., Li S, Zhang, C .*, Zheng B., and Tsung, F. 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). Springer, Cham, 2021: 321-336.

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

6. Zhang, C ., and Hoi, C.H. (2019). Online Learning for Partially Observable Multisensor Sequential Change Detection, 33rd AAAI Conference on Artificial Intelligence 2019 .

5. Wang, R., Chen, N. and Zhang, C . (2018). Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping, in 2018 IEEM , pp 531-535.

4. Zhang, C ., Zhang, L., and Chen, N. (2017). Spectral Network Approach for Multi-channel Profile Data Analysis with Applications in Advanced Manufacturing,in 2017 IEEM , pp. 1709-1713.

3. Zhang, C ., Chen, N., and Zhang, L. (2016). Time Series of Multivariate Zero-inflated Poisson Counts,in 2016 IEEM pp. 1365-1369.

2. Zhang, C ., and Chen, N. (2015). Statistical Monitoring of Longitudinal Categorical Survey Data, in 2015 IEEM pp. 1397-1401.

1. Zhang, C ., and Chen, N. (2014). Robust On-line Monitoring for Univariate Processes Based on Two Sample Goodness-of-fit Test,in 2014 IEEM pp. 813-817.