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Kaibo Liu

Kaibo Liu

Grainger STAR Professor

Dr. Kaibo Liu is currently the Grainger STAR Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison and serves as the Associate Director of the UW-Madison IoT Systems Research Center. He earned his B.S. degree in Industrial Engineering and Engineering Management from the Hong Kong University of Science and Technology, an M.S. degree in Statistics, and a Ph.D. degree in Industrial Engineering from the Georgia Institute of Technology. Dr. Kaibo Liu’s research is in system informatics and big data analytics, with an emphasis on the data fusion approach for system modeling, monitoring, diagnosis, prognostics, and decision making. His research has been successfully funded by NSF, ONR, AFOSR, ERDC, DOE, NIH, and Industry. He is the recipient of three prestigious early career awards, including the 2019 Outstanding Young Manufacturing Engineer Award by SME, the2019 Feigenbaum Medal Award by ASQ, and the 2019 Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award by IISE. He is also the winner of the Innovations in Education Award from IISE in 2020 and the Award for Technical Innovation in Industrial Engineering from IISE in 2021. He received the honor of Georgia Tech Alumni Association’s 40 Under 40 and Ragnar E. Onstad Service to Society Award from UW-Madison. Recently, he received the prestigious Hromi Medal Award from ASQ in 2024. Dr. Kaibo Liu is currently serving as a senior editor of IEEE Transactions on Automation Science and Engineering and as the focus issue editor of IISE Transactions on Data Science, Quality, and Reliability.

Department

Industrial & Systems Engineering

Contact

Mechanical Engineering Bldg
1513 University Ave
Madison, WI

  • PhD 2013, Georgia Institute of Technology
  • MS 2011, Georgia Institute of Technology
  • BS 2009, Hong Kong University of Science and Technology

  • System Informatics and Big Data Analytics
  • Data Fusion for Process Modeling, Monitoring, Diagnosis, Prognostics, and Decision Making
  • Statistical Learning, Machine Learning, and Data Mining
  • Statistical Process Control

  • 2024 American Society for Quality (ASQ), Hromi Medal Award
  • 2023 Industrial and Systems Engineering Research Conference (ISERC), DAIS Section, Best Paper Finalist award
  • 2023 Georgia Institute of Technology, Georgia Tech Alumni Association’s 40 Under 40
  • 2021 Institute of Industrial and Systems Engineers (IISE), Award for Technical Innovation in Industrial Engineering
  • 2020 IISE Transactions, Best Application Paper Award
  • 2020 IEEE Transactions on Automation Science and Engineering, Best New Application Paper Award (first runner-up)
  • 2020 IEEE Transactions on Automation Science and Engineering, Best Paper Award (second runner-up)
  • 2020 ISE Magazine, Feature Article
  • 2020 Institute of Industrial and Systems Engineers (IISE), Innovations in Education Award
  • 2019 Society of Manufacturing Engineers (SME), Outstanding Young Manufacturing Engineer Award
  • 2019 Quality, Statistics, and Reliability Section of INFORMS, Best Paper Award
  • 2019 Institute of Industrial and Systems Engineers (IISE), Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award
  • 2019 ISE Magazine, Feature Article
  • 2019 ISE Magazine, Feature Article
  • 2019 American Society for Quality (ASQ), Feigenbaum Medal Award
  • 2014 Institute of Industrial and Systems Engineers (IISE), Pritsker Doctoral Dissertation Award (2nd place)
  • 2013 American Society for Quality (ASQ), Richard A. Freund International Scholarship
  • 2012 Institute of Industrial and Systems Engineers (IISE), Gilbreth Memorial Fellowship

  • Li, H., Ye, H., Cheng, J. C., & Liu, K. (2024). Online Monitoring of Heterogeneous Partially Observable Data Streams Based on Q-Learning. IEEE Transactions on Automation Science and Engineering.
  • Ye, H., Zheng, Z., Cheng, J. C., Hable, B., & Liu, K. (2024). Online monitoring of high-dimensional asynchronous and heterogeneous data streams for shifts in location and scale. International Journal of Production Research, 62(3), 720--736.
  • Zheng, Z., Ye, H., & Liu, K. (2024). Online nonparametric monitoring for asynchronous processes with serial correlation. IISE Transactions, 1--14.
  • Xu, H., Xian, X., Zhang, C., & Liu, K. (2024). Partially-Observable Sequential Change-Point Detection for Autocorrelated Data via Upper Confidence Region. arXiv preprint arXiv:2404.00220.
  • 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.
  • Wang, D., & Liu, K. (2023). An integrated deep learning-based data fusion and degradation modeling method for improving prognostics. IEEE Transactions on Automation Science and Engineering.
  • Kim, M., Allen, T., & Liu, K. (2023). Covariate dependent sparse functional data analysis. INFORMS Journal on Data Science, 2(1), 81--98.
  • Wang, D., Li, F., & Liu, K. (2023). Modeling and monitoring of a multivariate spatio-temporal network system. IISE Transactions, 55(4), 331--347.
  • Ye, H., Xian, X., Cheng, J. C., Hable, B., Shannon, R. W., Elyaderani, M. K., & Liu, K. (2023). Online nonparametric monitoring of heterogeneous data streams with partial observations based on Thompson sampling. IISE Transactions, 55(4), 392--404.
  • Wang, D., Li, F., Liu, K., & Zhang, X. (2023). Real-time cyber-physical security solution leveraging an integrated learning-based approach: An integrated learning-based cyber-physical security solution. ACM Trans. Sensor Netw.

  • I SY E 412 - Fundamentals of Industrial Data Analytics (Spring 2025)
  • I SY E 612 - Information Sensing and Analysis for Manufacturing Processes (Spring 2025)
  • I SY E 699 - Advanced Independent Study (Spring 2025)
  • I SY E 890 - Pre-Dissertator's Research (Spring 2025)
  • I SY E 990 - Research and Thesis (Spring 2025)
  • I SY E 890 - Pre-Dissertator's Research (Fall 2024)
  • I SY E 990 - Research and Thesis (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 412 - Fundamentals of Industrial Data Analytics (Spring 2024)
  • I SY E 612 - Information Sensing and Analysis for Manufacturing Processes (Spring 2024)
  • I SY E 890 - Pre-Dissertator's Research (Spring 2024)
  • I SY E 990 - Research and Thesis (Spring 2024)
  • I SY E 699 - Advanced Independent Study (Fall 2023)
  • I SY E 890 - Pre-Dissertator's Research (Fall 2023)
  • I SY E 699 - Advanced Independent Study (Summer 2023)
  • I SY E 890 - Pre-Dissertator's Research (Summer 2023)