Xiaolei Fang

Assistant 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.


  • Data science
  • Machine learning


  • 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

Discover more about Xiaolei Fang




Lin, F., Fang, X., & Gao, Z. (2022). [Review of , ]. NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION. https://doi.org/10.3934/naco.2021057
Infrared image stream based regressors for contactless machine prognostics
Dong, Y., Xia, T., Wang, D., Fang, X., & Xi, L. (2021), MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 154. https://doi.org/10.1016/j.ymssp.2020.107592
Integrated Remanufacturing and Opportunistic Maintenance Decision-Making for Leased Batch Production Lines
Xia, T., Zhang, K., Sun, B., Fang, X., & Xi, L. (2021), JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME. https://doi.org/10.1115/1.4049963
Multichannel profile-based monitoring method and its application in the basic oxygen furnace steelmaking process
Qian, Q., Fang, X., Xu, J., & Li, M. (2021), JOURNAL OF MANUFACTURING SYSTEMS. https://doi.org/10.1016/j.jmsy.2021.09.010
Remaining useful life prediction based on a multi-sensor data fusion model
Li, N., Gebraeel, N., Lei, Y., Fang, X., Cai, X., & Yan, T. (2021), RELIABILITY ENGINEERING & SYSTEM SAFETY, 208. https://doi.org/10.1016/j.ress.2020.107249
Two-dimensional variable selection and its applications in the diagnostics of product quality defects
Jeong, C., & Fang, X. (2021), IISE TRANSACTIONS. https://doi.org/10.1080/24725854.2021.1904524
Multi-sensor prognostics modeling for applications with highly incomplete signals
Fang, X., Yan, H., Gebraeel, N., & Paynabar, K. (2020), IISE TRANSACTIONS. https://doi.org/10.1080/24725854.2020.1789779
Image-Based Prognostics Using Penalized Tensor Regression
Fang, X., Paynabar, K., & Gebraeel, N. (2019), TECHNOMETRICS, 61(3), 369–384. https://doi.org/10.1080/00401706.2018.1527727
Online Analytics Framework of Sensor-Driven Prognosis and Opportunistic Maintenance for Mass Customization
Xia, T., Fang, X., Gebraeel, N., Xi, L., & Pan, E. (2019), JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 141(5). https://doi.org/10.1115/1.4043255
Prognostic and health management for adaptive manufacturing systems with online sensors and flexible structures
Dong, Y., Xia, T., Fang, X., Zhang, Z., & Xi, L. (2019), COMPUTERS & INDUSTRIAL ENGINEERING, 133, 57–68. https://doi.org/10.1016/j.cie.2019.04.051

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Xiaolei Fang