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

Deep Complex Wavelet Denoising Network for Interpretable Fault Diagnosis of Industrial Robots With Noise Interference and Imbalanced Data
Li, R., Xia, T., Jiang, Y., Wu, J., Fang, X., Gebraeel, N., & Xi, L. (2025), IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 74. https://doi.org/10.1109/TIM.2025.3540131
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
IISE PG&E Energy Analytics Challenge 2024: Forecasting day-ahead electricity prices
Ezzat, A. A., Mansouri, M., Yildirim, M., & Fang, X. (2025, January 16), IISE TRANSACTIONS, Vol. 1. https://doi.org/10.1080/24725854.2024.2447049
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

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Xiaolei Fang