About Me

• Curriculum Vitae (CV)

Education

• National University of Singapore (NUS) (Aug. 2017 - Aug. 2021)
  • Ph.D. in Industrial Systems Engineering & Management
  • Supervisor: Assoc. Prof. YE Zhi-Sheng
• University of Science and Technology of China (USTC) (Sep. 2014 - July 2017)
  • Master in Instrument Science & Technology
  • Supervisor: Prof. HE Qingbo (Supported by Program for the Top Young Innovative Talents)
• Hunan University (HNU) (Sep. 2010 - July 2014)
  • Bachelor in Measurement & Control Technology & Instruments

Work Experience

• City University of Hong Kong (CityU) (Jan. 2022 - Dec. 2022)
  • Postdoc. in Advanced Design & Systems Engineering
  • Supervisor: Chair Prof. XIE Min (Academician of the European Academy of Sciences and Arts)

Research Interests

• Process Monitoring, Health Management, Reliability
• Machine Learning

Academic Achievements

Journal Papers (Accepted)

1. Liu, X., Du, J., & Ye, Z.-S. (2022). A covariate-regulated sparse subspace learning model and its application to process monitoring and fault isolation. Technometrics, tentatively accepted. (Top Journal in Industrial Statistics)
2. Liu, X., Du, J., & Ye, Z.-S. (2022). A condition monitoring and fault isolation system for wind turbine based on SCADA data. IEEE Transactions on Industrial Informatics, 18(2), 986–995. (Top Journal, IF=10.215)
3. Liu, X., Sun, Q., Ye, Z.-S., & Yildirim, M. (2021). Optimal multi-type inspection policy for systems with imperfect online monitoring. Reliability Engineering & System Safety, 207, 107335. (Top Journal, IF=6.188)
4. Liu, X., Hu, Z., He, Q., Zhang, S., & Zhu, J. (2017). Doppler distortion correction based on microphone array and matching pursuit algorithm for a wayside train bearing monitoring system. Measurement Science and Technology, 28(10), 105006.
5. Liu, X., Hu, Z., He, Q., & Zhu, J. (2017). Doppler distortion correction method based on rotation matching of time-frequency ridge lines. Journal of Vibration and Shock, 2017, 17.
6. Zhu, J., Wang, C., Hu, Z., Kong, F., & Liu, X. (2017). Adaptive variational mode decomposition based on artificial fish swarm algorithm for fault diagnosis of rolling bearings. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science,231(4), 635–654.
7. Hu, Z., Wang, C., Zhu, J., Liu, X., & Kong, F. (2016). Bearing fault diagnosis based on an improved morphological filter. Measurement,80, 163–178.

Journal Papers (Under Review)

8. Dai, L., Liu, X., Hu, Z., Mao, L., Huang, W., & Wu, Q. (2022). On-board SOH Estimation of Lithium-ion Batteries with Sequential Gaussian Process. IEEE Transactions on Industrial Informatics, under review.
9. Kong, J., Cui, D., Hou, B., Liu, X., & Wang, D. (2022). New Short-long-term Degradation Model for Precise Battery Health Prognostics. IEEE Transactions on Industrial Electronics, under review.
10. Yu,Y., Xiong, Q., Ye, Z.-S., Liu, X., Li,Q., & Wang K. (2022). Acoustic Reconstruction of Temperature Profiles: From Time Measurement to Reconstruction Algorithm. IEEE Transactions on Instrumentation and Measurement, under review.

Journal Papers (In Progress)

11. Degradation Modeling for Lithium-ion Battery under Calendar and Cyclic Aging with a Monotonic Spline-Based Wiener Process.
12. Degradation analysis using a novel Kalman filter with robustness to distributionally uncertainty and measurement outlier.

International Conferences

1. Liu, X., & Ye, Z.-S. (2021). A covariate-regulated sparse subspace learning model and its application to process monitoring and fault isolation. The 3rd International Conference on System Reliability and Safety Engineering (SRSE 2021).
2. Yang, L., Li, X., Liu, X., & Zhu, F., (2022). A Remaining Useful Life Prediction Framework for Aero-engine Using Information Entropy-based Criterion and PCA-RVM. The 13th International Conference on Reliability, Maintainability, and Safety (ICRMS 2022).