James Hopgood

Director of Electronics and Electrical Engineering

Email: James.Hopgood@ed.ac.uk

James is the Director of Electronics and Electrical Engineering (EEE) within the School of Engineering and Institute for Digital Communications, at the University of Edinburgh. As Director of EEE, James provides strategic leadership to further develop the international excellence of the School’s work in Electronics and Electrical Engineering, leading a team of more than 40 academics.

James research specialism is in Data Science and Machine Learning within the field of Statistical Signal Processing. His research spans a diverse range of applications, from medical imaging to audio processing in adverse acoustic environments, through to underwater imaging, multi-modal sensor-fusion, and multi-target tracking. In the life-sciences, James has developed signal processing solutions for gel-electrophoresis, spectral analysis techniques for SERS, and super-resolution for ultrasound. James is a member of Advisory Board for Firefinch, an Edinburgh based company for Bespoke Software and Data Science solutions for Life Sciences and Manufacturing.

Current research projects include Microendoscopy Imaging on EPSRC EP/S025987/1, “Next-Generation Sensing For Human In Vivo Pharmacology- Accelerating Drug Development In Inflammatory Diseases”, and EPSRC EP/S000631/1 project, “Signal Processing in the Information Age”.  James is Editor-in-Chief for the IET Journal of Signal Processing.

Outside of work, James has a keen interest in outdoor activities, especially with his wife and young son.



Fast and robust single-exponential decay recovery from noisy fluorescence lifetime imaging (2022).
Taimori A, Humphries D, Williams G, Dhaliwal K, Finlayson N, Hopgood J R.


Deep Learning-Assisted Co-registration of Full-Spectral Autofluorescence Lifetime Microscopic Images with H&E-Stained Histology Images (2022).
Wang Q, Fernandes S, Williams G, Finlayson N, Akram A R, Dhaliwal K, Hopgood J R, Vallejo M.


Multi-Scale Aggregated-Dilation Network for ex-vivo Lung Cancer Detection with Fluorescence Lifetime Imaging Endomicroscopy (2021).
Wang Q, Hopgood J R, Vallejo M.


Deep Learning in ex-vivo Lung Cancer Discrimination using Fluorescence Lifetime Endomicroscopic Images (2020).
Wang Q, Hopgood JR, Finlayson N, Williams GO, Fernandes S, Williams E, Akram A, Dhaliwal K, Vallejo M


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