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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

Fingerprint Dive into the research topics where Panagiotis Zacharis is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 22 Similar Profiles
Ultrasonics Engineering & Materials Science
Inspection Engineering & Materials Science
Defects Engineering & Materials Science
inspection Physics & Astronomy
ultrasonics Physics & Astronomy
tubes Physics & Astronomy
Outages Engineering & Materials Science
Condition monitoring Engineering & Materials Science

Research Output 2017 2019

Automated pressure tube defect analysis

Zacharis, P., West, G., Wallace, C., Dobie, G. & Gachagan, A., 9 May 2019. 1 p.

Research output: Contribution to conferencePoster

Open Access
File
Defects
Knowledge based systems
Testing
Automation
Inspection
Open Access
File
Outages
Inspection
Ultrasonics
Defects
Testing