Professor Graeme West

Electronic and Electrical Engineering

Personal statement

I am a Professor in the Department of Electronic and Electrical Engineering, having been appointed through the Chancellor's Fellowship scheme. My research interests lie in the area of intelligent decision support, primarily for applications in the Energy Industry, and with a particular focus on through lifetime management of nuclear power generation assets. This covers a broad range of disciplines ranging from artificial intelligence, machine learning, & data analytics through to image and video processing. Application areas include inspection, condition monitoring, diagnostics and prognostics of plant items, both from individual asset and fleet wide perspectives. I am an academic lead in the University’s Advanced Nuclear Research Centre (ANRC).

My current projects at the University include improving understanding of the graphite reactor cores of Advanced Gas-cooled Reactors (AGR) through analysis of refuelling data (EDF Energy), Automated sizing and classification of defects in CANDU reactor pressure tubes (Bruce Power), improved visual inspection of AGR fuel channel bricks (EDF Energy) and visual inspection of steel pipe work in the nuclear industry (NNL, Sellafield, WideBlue, Inspecta-hire).

I am also seconded part time to the Alan Turing Institute, where I lead the Critical Infrastructure Theme in the Data Centric Engineering Programme

Expertise

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Area of Expertise

Intelligent Systems and Artificial Intelligence
Data Analytics and Machine Learning
Condition Monitoring, Diagnostics and Prognostics
Nuclear power generation instrumentation and control

Publications

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Publications

Machine learning and knowledge-driven approaches for automated Calandria Tubesheet Bore Inspection in CANDU reactors: Young Andrew, Manning Callum Paul, Zabalza Jaime, West Graeme, Murray Paul, McArthur Stephen, Kennedy Chris, Barpugga Harpreet; Sixth Annual Conference on Disruptive, Innovative, and Emerging Technologies in the Nuclear Industry: DIET 2025 (2025)
Temporal denoising algorithms for radiation-affected nuclear inspection video footage: Young Andrew, Devereux Michael, Zabalza Jaime, West Graeme; Universities’ Nuclear Technology Forum 2025 (2025)
Real world video denoising for visual inspection in high-dose radiological environments: Young Andrew, Fei Zhouxiang, Zabalza Jaime, West Graeme M, Murray Paul, McArthur Stephen D J; Nuclear Technology Vol 211, pp. 1448-1458 (2025); https://doi.org/10.1080/00295450.2024.2410610
Knowledge-driven explainable AI for automated defect detection in nuclear reactor components: Young Andrew, Zabalza Jaime, Fei Zhouxiang, West Graeme, Murray Paul, McArthur Stephen; 14th International Topical Meeting on Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies (NPIC&HMIT 2025) (2025)
Predictive monitoring of asset populations in a rotating plant under operational uncertainty : a transfer learning approach: Ghauch Ziad, Young Andrew, Brown Blair David, Stephen Bruce, West Graeme, McArthur Stephen, Duncan Andrew; Data-Centric Engineering Vol 6 (2025); https://doi.org/10.1017/dce.2025.3
Leveraging Knowledge Graphs for explainable predictive maintenance strategies: Manning Callum Paul, West Graeme, Young Andrew, McArthur Stephen; Fifth Annual Conference on Disruptive, Innovative, and Emerging Technologies in the Nuclear Industry (2024)

More publications

Teaching

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Teaching

I am module registrar for EM501: Fifth Year Group Projects for the MEng Electrical and Mechanical Engineering Students.

I am module registrar for the 3rd Year EM310: Signal and Systems course which covers the concepts and analysis of signals in both the time and frequency domains in the context of both analogue and discrete (digital) domains, both in terms of mathematical analysis and practical systems.

Research

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Research Interests

My research interests are in the design and application of artificial intelligence techniques to support the management of key engineering assets in a number of industries. I have a particular focus in nuclear power generation applications and my research supports EDF Energy, who run and maintain the UK's Civil nuclear power stations, in analysing data that comes from their graphite reactor cores.