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Chen Zhang, Associate Professor


Name: Chen Zhang Phone: +86-10-62796135 E-mail: Fax: Address: 602 Shunde building, Tsinghua University, Beijing, 100084 Homepage:


I am an Associate Professor in Industrial Engineering, Tsinghua University. I received my Ph.D. degree from National University of Singapore in 2017, and my B.Eng. degree from Tianjin University in 2012. My research interests include developing methodologies and algorithms for complex or large-scale systems with multivariate or high-dimensional data, including intelligent sampling and sensing for data collection, data mining and information extraction for system modeling, and on-line monitoring and efficient anomaly detection for streaming data.

Research Opportunities and Job Vacancy: I am now looking for self-motivated Ph.D. students with strong math and coding background. I am also hiring Postdoc, Research Assistants/Associates for exciting machine learning research and industry-scale data science project. Interested applicants, please email your CV to:

Honors and Awards

ASQ Brumbaugh Award, 2019
IISE Transactions, Best Paper Award, 2018
National Semiconductor Gold Metal, Singapore, 2018
INFORMS Data Mining Section Best Paper Award, 2017
NFORMS Quality, Statistics, and Reliability Section Best Student Poster Award, 2016
Singapore Government Research Scholarship, 2013 to 2017
Distinguished Undergraduates, Tianjin University, 2012

Educational Background

Ph.D.                     Industrial Systems Engineering and Management, National University of Singapore, 2017
Visiting student     Industrial & Systems Engineering, Georgia Institute of Technology, 2016
B.E.                       Electronic Science and Technology, Tianjin University, 2012

Employment History

Associate Professor, Industrial Engineering, Tsinghua University, 2020 - now
Assistant Professor, Industrial Engineering, Tsinghua University, 2018 - 2020
Research Fellow, Information Systems, Singapore Management University, 2017- 2018


Undergraduate Level:
•Machine Learning and Big Data
•Engineering Economy

Graduate Level:
•Advanced Quality Management    

Research Interests

Statistical modeling and monitoring for complex systems
Machine learning and data mining techniques for large-scale systems
On-line learning and real-time monitoring for streaming data analysis

Research Projects

NSFC: Multi-channel Profile Modeling and Monitoring based on Machine Learning Algorithms, 2020-2022, PI
NSFC: Towards High-Quality Intelligent Manufacturing -- Quality Science Research under Industrial, Big-data Environment, 2020-2023, Co-PI    


Referred Journals and Transactions:

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.


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.



Department of Industrial Engineering, Tsinghua University
Phone: 010-62772989
Address:Shunde Building, Tsinghua University, Beijing 100084

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