Professor Stephen McKenna

Stephen McKenna
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Professor McKenna graduated in Computer Science from the University of Edinburgh and obtained his PhD from the University of Dundee. Following an EU research fellowship in Italy he was an EPSRC postdoctoral researcher at Queen Mary, University of London, and held visiting research positions at BT Advanced Perception Lab, George Mason University, and Universidad Iberoamerica. He was the British Association’s Isambard Kingdom Brunel Award Lecturer in 2001. He was promoted to Senior Lecturer in 2004 and to a Personal Chair in 2008. 

Professor McKenna has chaired the British Machine Vision Conference (BMVC), the Medical Image Understanding and Analysis (MIUA) conference, and several research workshops. He has served on numerous programme committees, guest edited journal issues, and served on various editorial boards, currently including the journal Scientific Data. He has chaired research funding panels for the Academy of Finland, served on panels for EPSRC and BBSRC, and reviewed numerous proposals for national and international funding agencies. He has been an EPSRC College member since 2002.

He currently leads the Computer Science and Informatics research cluster in the School of Science and Engineering. He coordinated the University of Dundee’s Computer Science and Informatics submission to the Research Excellence Framework (REF) in 2021. 


Professor McKenna’s research interests are predominantly in biomedical image analysis, machine learning, pattern recognition, computer vision, and data science. He has received funding from NIHR, EPSRC, MRC, BBSRC, Innovate UK, Scottish Enterprise, the Chief Scientist Office, and charities. He has won international pattern recognition challenges associated with ICPR and MICCAI.

His PhD thesis (1994) developed machine learning for image analysis in cancer screening, incorporating convolutional neural nets. His post-doctoral work focused on computer vision for face and gesture recognition. Since then his research has developed in the context of many and varied application domains, in collaborations with other disciplines, clinicians, museums, large companies, and SMEs. These include:

  • Dermatology: artificial intelligence for skin lesion diagnosis in real-world clinical settings (with NHS Tayside)
  • Disease biomarkers: multi-modal (retinal-clinical-genetic) biomarkers for cardiovascular disease (with Dundee and Edinburgh clinicians and the VAMPIRE initiative) 
  • Digital pathology: immuno-histochemical scoring, tumour segmentation, analysis of 3D optical projection imaging of polyps, and whole-slide image analysis (with pathology and oncology, Ninewells Hospital)
  • Assistive technology: multi-sensor perception for augmenting communication using environmental data-driven language prediction (the ACE-LP project with the AAC research group, Edesix Ltd., Smartbox, Tobii Dynavox, and Arria NLG Ltd) 
  • Industrial inspection: computer vision for post-mortem inspection in food production (with Newcastle University, Tulip Ltd. and Hellenic Systems Ltd), and computer vision for inspection of electricity towers (with Mechanical and Industrial Engineering)
  • Cell and plant biology: microscopy image analysis (with Lucocq and Swedlow) and analysis of plant root growth (with SCRI, now the James Hutton Institute)
  • Surgery: image analysis for assessment of acetabular wear, osteoarthritis monitoring, visual tracking of laparoscopic surgical instruments, and 3D sonoelastograhic breast imaging (with Cuschieri, Frank, Carter, Wigderowitz, Ninewells Hospital and Medical School)
  • Automotive: computer vision for control of in-vehicle secondary systems (with Daewoo Motor Co. Ltd., Vision Dynamics Ltd., University of Derby)
  • Cultural Heritage, Fashion, and Digital Art: software for exploration and visualisation of archival image collections (the FABRIC project with Liberty Art Fabrics Ltd, Systems Simulation Ltd, and the V&A), the GVision computer vision art installation (with artist Nigel Johnson), and developing the algorithm behind the award-winning Horizon Screen (National Maritime Museum, London)

Professor McKenna jointly leads the CVIP research group. He greatly enjoys working with post-docs and PhD students. 

View full research profile and publications


Professor McKenna has extensive experience in the development, coordination, and delivery of teaching across a range of topics in computing at both undergraduate and postgraduate levels. He is a Fellow of the Higher Education Academy. He was programme director for the Intelligent Computational Systems MSc. He currently teaches on Masters level modules in Machine Learning, Data Science, and AI in Healthcare. He also supervises undergraduate (BSc Hons) and postgraduate (MSc) student projects each year on topics related to his research interests, some of which have led to student co-authorship of research publications or national student awards.

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Areas of expertise

  • AI/automation
  • Technology

Second supervisor