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Personal profile

Personal Statement

I am a Research Associate at the University of Strathclyde in the department of Electronic and Electrical Engineering. My current research is concerned with providing decision support tools for the health assessment of pressure tubes, a critical component of CANDU reactors, by fusing formalised elicited expert konwledge with machine learning and deep learning methods.

My background is in computational algorithms and optimisation techniques applied to physical problems and analytically intractable tasks. I received my B.Sc. degree in Physics from Aristotle University in 2012 and my M.Sc. in Scientific Computation from University of Nottingham in 2014. My Ph.D. focused on Data-driven analysis of multi-probe ultrasonic inspection datasets of CANDU pressure tubes. 

Research Interests

  • Unsupervised machine learning
  • Deep learning
  • Anomaly detection
  • Signal processing
  • Condition monitoring
  • Ultrasonic analysis


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