Skip to main content
Shiyu Zhou

Shiyu Zhou

David H. Gustafson Department Chair
Vilas Distinguished Achievement Professor

Shiyu Zhou is the David H. Gustafson Chair and Vilas Distinguished Achievement Professor of the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research focuses on data-driven modeling, monitoring, diagnosis, and prognosis for engineering systems with particular emphasis on manufacturing and after-sales service systems. He has established methods for modeling, analysis, and control of Internet-of-Things (IoT) enabled smart and connected systems, variation modeling, analysis, and reduction for complex manufacturing processes, and process control methodologies for emerging nano-manufacturing processes. He is a recipient of CAREER Award from the National Science Foundation and multiple Best Paper Awards. He is a fellow of IISE, ASME, and SME.

Department

Industrial & Systems Engineering

Contact

3254, Mechanical Engineering Bldg
1513 University Ave
Madison, WI

Featured news

  • MS 2000, University of Michigan
  • PhD 2000, University of Michigan
  • MS 1996, University of Science and Technology of China
  • BS 1993, University of Science and Technology of China

  • Modeling and analysis of the variation propagation and other in-process sensing data in complex manufacturing processes.
  • In-process quality and productivity improvement: diagnosis of complicated manufacturing processes using sensor fusion, feature extraction, and pattern recognition based on engineering field knowledge.
  • Fast calibration and active compensation for manufacturing systems: active real-time control of manufacturing processes, integration of statistical process control with automatic process control.

  • 2024 College of Engineering, University of Wisconsin-Madison, David H. Gustafson Department Chair, Industrial and Systems Engineering
  • 2023 IISE , IISE Transactions Best Paper Award
  • 2023 IISE Annual Conference, QCRE Best Student Paper finalist (Nominated)
  • 2022 IISE Transactions, Best Paper Honorable Mention
  • 2021 IISE Transactions, Best Paper Award
  • 2021 IISE Transactions, Best Paper Honorable Mention
  • 2020 College of Engineering, University of Wisconsin-Madison, Ragnar E. Onstad Service to Society Award
  • 2017 Quality, Statistics, and Reliability (QSR) Track, INFORMS, Best student paper award
  • 2017 IISE, Fellow
  • 2017 SME, Fellow
  • 2015 ASME, Fellow
  • 2015 QSR Track, INFORMS, Finalist of best student paper award (Nominated)
  • 2010 INFORMS, Best student paper award, QSR Track
  • 2009 QSR Track, INFORMS, Finalist of best student paper award (Nominated)
  • 2006 IIE Transactions, Best Application Paper Award
  • 2006 National Science Foundation, NSF CAREER Award
  • 2003 SME , SME Education Foundation Research Initiation Award
  • 2000 College of Engineering (CoE), University of Michigan, Distinguished Achievement Award
  • University of Wisconsin-Madison, Vilas Distinguished Achievement Professorship

  • Bansal, V., Chen, Y., & Zhou, S. (2024). Component-wise Markov decision process for solving condition-based maintenance of large multi-component systems with economic dependence. IISE Transactions, 1–14 https://doi.org/10.1080/24725854.2023.2295376
  • Huang, C., Blondheim, D., & Zhou, S. (2024). A Comparison Study on Anomaly Detection Methods in Process Monitoring with X-ray Images. Journal of Intelligent Manufacturing, in press.
  • Bansal, V., Chen, Y., & Zhou, S. (2024). A Rollout Approach for Condition-Based Maintenance of Large Multi-Unit Systems. Quality and Reliability Engineering International, submitted.
  • Huh, Y. K., Kim, M., Liu, K., & Zhou, S. (2024). An Integrated Uncertainty Quantification Model for Longitudinal and Time-to-event Data. IEEE Transactions on Automation Science and Engineering, conditionally accepted.
  • Hu, H., Bansal, V., Zhou, S., & Chen, Y. (2024). Condition based maintenance of k-out-of-n system. IEEE Transactions on Reliability, submitted.
  • Huang, C., Sun, J., Zhou, S., & Liu, K. (2024). Constraint Gaussian Process Model for System Degradation Prediction. IISE Transactions, to be submitted.
  • Bansal, V., & Zhou, S. (2024). Hidden Markov Model with Deep Neural Network as Observation Models. IISE Transactions, to be submitted.
  • Sun, J., Zhou, S., Veeramani, D., & Liu, K. (2024). Prediction of Condition Monitoring Signals Using Scalable Pairwise Gaussian Processes and Bayesian Model Averaging. IEEE Transactions on Automation Science and Engineering.
  • Huang, C., Zhou, Shiyu Li, Jingshan,, & Radwin, R. G. (2024). Reinforcement Learning based Production System Task Allocation with Cobots. IEEE Transactions on Automation Science and Engineering, to be submitted.
  • Sun, J., Zhou, S., & Veeramani, D. (2023). A neural network-based control chart for monitoring and interpreting autocorrelated multivariate processes using layer-wise relevance propagation. Quality Engineering, 35(1), 33--47 https://doi.org/10.1080/08982112.2022.2087041

  • I SY E 699 - Advanced Independent Study (Spring 2025)
  • I SY E 890 - Pre-Dissertator's Research (Spring 2025)
  • I SY E 510 - Facilities Planning (Fall 2024)
  • I SY E 890 - Pre-Dissertator's Research (Fall 2024)
  • M E 510 - Facilities Planning (Fall 2024)
  • I SY E 699 - Advanced Independent Study (Summer 2024)
  • I SY E 890 - Pre-Dissertator's Research (Summer 2024)
  • I SY E 990 - Research and Thesis (Summer 2024)
  • I SY E 512 - Inspection, Quality Control and Reliability (Spring 2024)
  • I SY E 603 - Special Topics in Engineering Analytics and Operations Research (Spring 2024)
  • I SY E 699 - Advanced Independent Study (Spring 2024)
  • I SY E 790 - Master's Research and Thesis (Spring 2024)
  • I SY E 990 - Research and Thesis (Spring 2024)
  • M E 512 - Inspection, Quality Control and Reliability (Spring 2024)
  • I SY E 510 - Facilities Planning (Fall 2023)
  • I SY E 699 - Advanced Independent Study (Fall 2023)
  • I SY E 790 - Master's Research and Thesis (Fall 2023)
  • I SY E 990 - Research and Thesis (Fall 2023)
  • M E 510 - Facilities Planning (Fall 2023)
  • I SY E 699 - Advanced Independent Study (Summer 2023)
  • I SY E 990 - Research and Thesis (Summer 2023)