Deputy Head of Department (Research, Impact and Innovation)
Research Area: Intelligent Systems and Nano-science Group
Areas of Expertise: Evolutionary Algorithms, Intelligent Medical Devices, Biomedical Image Analysis
Stephen is currently a Professor in the Department of Electronic Engineering at the University of York, has a BSc in Computer Science, an MSc (by Research) and PhD in Electronic Engineering . His research has always been concerned with the application of computers to problems in healthcare. His current research interests include developing novel representations for evolutionary algorithms, particularly applied to the diagnosis of neurological dysfunction and analysis of mammograms. Stephen has authored over 75 refereed publications, is a Chartered Engineer and a Fellow of the British Computer Society. He is an Associate Editor for the journal Genetic Programming and Evolvable Machines and a member of the editorial board for the International Journal of Computers in Healthcare and Neural Computing Applications.
Publications information is available via the York Research Database
I am on study leave until September 2016.
Evolutionary computation takes inspiration from biology to develop new methods of computer programming that deliver solutions to unusual and difficult problems. My work is concerned with the theory of evolutionary computation and its application to real world problems, particularly signal processing and clinical diagnosis. Specifically, I am investigating alternative representations for Cartesian genetic programming (CGP) that make it more suitable for these applications. Commercial exploitation of my work is currently being supported through awards made by the Royal Academy of Engineering, the Centre for Chronic Diseases and Disorders at the University of York, Parkinson's UK, and Innovate UK.
Current work is concerned with the automated assessment of Parkinson’s disease and other neurodegenerative conditions based on the measurement and analysis of movement disorders and visuo-spatial ability. Features associated with symptoms of these neurological conditions are used to train novel evolutionary algorithms to aid diagnosis, monitoring and administration of medication. This technology has the potential to transform clinical practice allowing patients to be monitored with greater accuracy than previously possible in hospital and their own homes, leading the way to saving money and improving the patient’s quality of life. My ambition to see this technology made widely available has been realized through the creation of a University spin out company ClearSky Medical Diagnostics Ltd. (www.clearskymd.com) undertaken as part of a Royal Academy of Engineering Enterprise Fellowship awarded in 2012.
Four devices developed by my group are now in clinical use in leading medical centres worldwide, the result of collaborations I initiated with the University of California San Francisco Memory and Aging Center; Veterans Affairs Medical Center, San Francisco; Monash University Medical Centre, Melborne, Australia; Rashid Hospital, Dubai and the National Neuroscience Institute in Singapore, as well as Leeds and Liverpool hospitals in the UK.
Neural Computing and Applications – Editorial Board Member
Genetic Programming and Evolvable Machines - Associate Editor
International Journal of Computers in Healthcare – Editorial Board Member