Xiaolei Fang

Associate Professor

 
Xiaolei Fang‘s research interest lies in the field of industrial data analytics for high-dimensional and big data applications in the energy, manufacturing, and service sectors.

Methodologies:

  • Data science
  • Machine learning

Applications:

  • System performance assessment and optimization
  • System anomalies detection
  • Fault root causes diagnostics
  • Remaining useful lifetime prediction
  • Decision-making and control

Research Interests:

  • Addressing analytical, computational, and scalability challenges
  • Development of statistical and optimization methodologies
  • Analyzing massive amounts of complex data structures
  • Real-time asset management and optimization

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Publications

A distributionally robust chance-constrained kernel-free quadratic surface support vector machine
Lin, F., Fang, S.-C., Fang, X., Gao, Z., & Luo, J. (2024), EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 316(1), 46–60. https://doi.org/10.1016/j.ejor.2024.02.022
A federated data fusion-based prognostic model for applications with multi-stream incomplete signals
Arabi, M., & Fang, X. (2024, June 10), IISE TRANSACTIONS, Vol. 6. https://doi.org/10.1080/24725854.2024.2360619
Distributionally robust chance-constrained kernel-based support vector machine
Lin, F., Fang, S.-C., Fang, X., & Gao, Z. (2024), COMPUTERS & OPERATIONS RESEARCH, 170. https://doi.org/10.1016/j.cor.2024.106755
Image-based remaining useful life prediction through adaptation from simulation to experimental domain
Wang, Z., Yang, L., Fang, X., Zhang, H., & Xie, M. (2025), RELIABILITY ENGINEERING & SYSTEM SAFETY, 255. https://doi.org/10.1016/j.ress.2024.110668
Learning Undergraduate Data Science Through a Mobile Device and Full Body Movements
Jung, S., Wang, H., Su, B., Lu, L., Qing, L., Fang, X., & Xu, X. (2024, November 27), TECHTRENDS, Vol. 11. https://doi.org/10.1007/s11528-024-01026-0
Machine identity authentication via unobservable fingerprinting signature: A functional data analysis approach for MQTT 5.0 protocol
Koprov, P., Fang, X., & Starly, B. (2024), JOURNAL OF MANUFACTURING SYSTEMS, 76, 59–74. https://doi.org/10.1016/j.jmsy.2024.07.003
Tensor-based statistical learning methods for diagnosing product quality defects in multistage manufacturing processes
Jeong, C., Byon, E., He, F., & Fang, X. (2024, August 9), IISE TRANSACTIONS, Vol. 8. https://doi.org/10.1080/24725854.2024.2385670
Sparse Hierarchical Parallel Residual Networks Ensemble for Infrared Image Stream-Based Remaining Useful Life Prediction
Jiang, Y., Xia, T., Fang, X., Wang, D., Pan, E., & Xi, L. (2023), IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 19(10), 10613–10623. https://doi.org/10.1109/TII.2022.3229493
Systems and methods for authenticating manufacturing Machines through an unobservable fingerprinting system
Koprov, P., Gadhwala, S., Walimbe, A., Fang, X., & Starly, B. (2023), Manufacturing Letters, 35, 1009–1018. https://doi.org/10.1016/j.mfglet.2023.08.051
A convex two-dimensional variable selection method for the root-cause diagnostics of product defects
Zhou, C., & Fang, X. (2023), RELIABILITY ENGINEERING & SYSTEM SAFETY, 229. https://doi.org/10.1016/j.ress.2022.108827

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Xiaolei Fang