Dr. David Windridge is Associate Professor in Computer Science at Middlesex and heads the University's Data Science activities. His research interests centre on the related fields of machine-learning (A.I.), cognitive systems and computer vision (he also has a former research interest in astrophysics having obtained his Ph.D. in Cosmology at the University of Bristol).
He has authored and played a leading role on a number of large-scale machine-learning projects in academic and industrial research settings (including the EU DREAMS4CARS, EPSRC ACASVA and EU DIPLECS projects). He is also interested in cross-over areas of data science and has won a number of interdisciplinary research grants in areas as diverse as psychological modelling and proteomic classification. He is a Visiting Professor at Trento University, Italy, and a visiting Senior Lecturer at the University of Surrey. He has authored more than 100 peer-reviewed publications.
Juddo, Suraj and George, Carlisle and Duquenoy, Penny and Windridge, David (2018) Data governance in the health industry: investigating data quality dimensions within a big data context. Applied System Innovation, 1 (4).
Windridge, David and Kammueller, Florian (2018) Edit distance Kernelization of NP theorem proving for polynomial-time machine learning of proof heuristics. In: FICC 2019: Future of Information and Communications Conference, 14-15 Mar 2019, San Francisco, USA. (Accepted/In press)
Windridge, David and Mengoni, Riccardo and Nagarajan, Rajagopal (2018) Quantum error-correcting output codes. International Journal of Quantum Information . p. 1840003. ISSN 1793-6918 (Published online first)
Windridge, David and Thill, Serge (2018) Representational fluidity in embodied (artificial) cognition. Biosystems, 172 . pp. 9-17. ISSN 0303-2647
Aljrees, Turki and Shi, Daming and Windridge, David and Wong, B. L. William (2016) Criminal pattern identification based on modified K-means clustering. 2016 International Conference on Machine Learning and Cybernetics (ICMLC), 2 . pp. 799-806. ISSN 2160-1348