Research output per year
Research output per year
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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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.
- 1 Similar Profiles
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Automated pressure tube defect analysis
Zacharis, P., West, G., Wallace, C., Dobie, G. & Gachagan, A., 9 May 2019. 1 p.Research output: Contribution to conference › Poster
Open AccessFile35 Downloads (Pure) -
Experience, testing and future development of an ultrasonic inspection analysis defect decision support tool for CANDU reactors
Wallace, C., West, G., Zacharis, P., Dobie, G. & Gachagan, A., 13 Feb 2019. 10 p.Research output: Contribution to conference › Paper › peer-review
Open AccessFile24 Downloads (Pure)
Thesis
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Unsupervised data-driven analysis of ultrasonic inspection data
Author: Zacharis, P., 18 Apr 2023Supervisor: West, G. (Supervisor) & Dobie, G. (Supervisor)
Student thesis: Doctoral Thesis