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Personal profile

Research Interests

  • Fault diagnosis and condition monitoring
  • Cost-effective wireless condition monitoring system 
  • Data compression and signal processing
  • Machine learning
  • Energy harvesting


Xiaoli Tang is currently a Machine Learning and Data Scientist - KTP Associate in College of Engineering & Physical Sciences. She was a research fellow of the School of Engineering and Technology at Aston University who worked in Optimising Wheel Alignment to Reduce Vehicle Particulate Emissions project funded by Innovate UK from April 2020 to July 2021. She has a strong background in the research field of rotating machine condition monitoring. She has rich experience in developing data fusion and compression methods, effective and efficient fault diagnosis approaches, vibroacoustic instrumentation and testing, intelligent online wireless condition monitoring systems.

Education/Academic qualification

PhD, University of Huddersfield

11 Jan 201610 Jan 2020

Award Date: 16 Sep 2020


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