I am a Research and Applications Engineer at Baugh & Weedon NDE, where I specialise in low-frequency vibration testing and ultrasonic inspection techniques. My work focuses on developing and applying advanced non-destructive evaluation (NDE) methods to solve practical engineering challenges across a range of industries.
I earned my PhD at the University of Bristol as part of the FIND CDT programme, where I received doctoral training in sensing, imaging and analysis for the vital fields of NDE. This training was complemented by engagement with real-world case studies and their practical implications, giving me broad exposure to techniques such as ultrasonic NDT, radiography, optical and thermal imaging, and electromagnetic methods, thereby giving me a multidisciplinary perspective on NDT techniques.
My current research interests lie at the intersection of automation, data science, and inspection technology. I am particularly focused on leveraging machine learning and advanced data analysis to enhance the reliability and diagnostic capability of low-frequency NDE methods. By integrating predictive decision support systems, I aim to push low-frequency NDE toward greater efficiency, accuracy, and consistency, ultimately enabling earlier detection of potential issues and more informed engineering decisions.