Industrial Statistics and Data Analytics Lab

Industrial Statistics and Data Analytics Lab

Industrial Statistics and Data Analytics Lab, Department of Industrial Engineering, Tsinghua University

Publications

Referred Journals

  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.
  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.
  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.

Peer-reviewed Conference Proceedings

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Li, Z., Yan, H., Zhang, C. and Tsung, F. (2020), Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction, 34th AAAI Conference on Artificial Intelligence, 4804-4810.
  6. Zhang, C., and Hoi, C.H.* (2019), Online Learning for Partially Observable Multisensor Sequential Change Detection, 33rd AAAI Conference on Artificial Intelligence, 5733-5740.

Submitted Papers

  1. Huang, J., Xu, H., Zhang, C.*, Function-on-Function Gaussian Process with Application in Robust Parameter Design, INFORMS Journal on Computing, minor revision.
  2. Liu, P., Guo, J., Zhang, C.*, Spatial In-Profile Monitoring via Latent Tensor Gaussian Process with Mixed Effects, Technometrics, major revision.
  3. Guo, J., Liu, P., Zhang, C.*, Change Detection in Partially Observable Dynamic Network, Heterogeneous Multivariate Functional Time Series Modeling: A State Space Approach, IEEE Transactions on Knowledge and Data Engineering, major revision.
  4. Lan, T., Xu, H., Li, Z., Qiao, X., Tsung, F., Zhang, C.*, MultiFun-DAG: Multivariate Functional Directed Acyclic Graph Based on Causal Decomposition, INFORMS Journal on Computing, major revision.
  5. Du, J.*, Xie, Y., Zhang, C., COMPILED: Deep Metric Learning for Defect Classification of Threaded Pipe Connections using Multichannel Partially Observed Functional Data, Journal of Quality Technology, major revision.
  6. Xu, H., and Zhang, C.*, Functional-Edged Network Modeling, Technometrics, under review.
  7. Xu, H., Xian, X., Zhang, C.*, Liu, K., Change Detection for Partially Observable Linear Dynamic Systems with Adaptive Sampling via Upper Confidence Region, Naval Research Logistics, under review.
  8. Xu, H., Zhang, Q., Zhang, C.*, FRCOMA: Nonparametric Regression for Continuous Multi-way Data, IEEE Transactions on Signal Processing, under review.
  9. Mao, R., Wang, K.*, Zhang, C., Tsung, F., Common Components or Individual Ones or Between? A Partially Linked Multi-Matrix Decomposition for Joint Modeling of Multivariate Heterogeneous Profile Data, IISE Transactions, under review.