Paul Byrnes

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I received a BSc in Mathematics from the University College Cork, and graduated in May 2014. Following this, I studied for a MSc in Financial Economics. I began my PhD at the University of Liverpool in September 2016 in Statistical Machine Learning.

Research Interests: Supervised Machine Learning, Data Visualization, Noisy Data, Uncertainty Quantification.

Research project title: A Supervised Machine Learning Approach for Structural Health Monitoring (SHM)

Project description: Broadly speaking, damage identification and SHM can be achieved either through model-driven approaches (usually finite element analysis) or data-driven approaches, via a statistical representation of the structure or system . An important type of data-driven approach in machine learning is classification, where the aim is to assign an input pattern to one member of a set of classes. Our industrial partner is interested in developing methods for SHM in off-shore wind turbines. A data-driven damage detection approach such as probabilistic classification could provide the necessary guidance in order to achieve optimum repair costs and reliable structural integrity assessment.

Supervisory team: Alex Diaz, Simon Maskell, Sui Kui Au

ORCID: 0000-0002-4075-8591

Current employer: Apple
Position: Commercial Data Scientist