Dr. David Windridge is Senior Lecturer 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 EPSRC ACASVA and EU DIPLECS projects). He is particularly 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 Research Fellow at the University of Surrey (he was previously a Senior Research Fellow within the Centre for Vision, Speech and Signal Processing). He has authored more than 80 peer-reviewed publications.
Attfield, Simon and Hewitt, Daniel and Xu, Kai and Passmore, Peter J. and Wagstaff, Adrian and Phillips, Graham and Windridge, David and Dash, Greg and Chapman, Richard and Mason, Lee (2016) Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines. In: IEEE VAST Challenge 2016, 23 Oct 2016, Baltimore, MD, USA.
Tirunagari, Santosh and Poh, Norman and Wells, Kevin and Bober, Miroslaw and Gorden, Isky and Windridge, David (2017) Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition. Machine Vision and Applications, 28 (3-4). pp. 393-407. ISSN 0932-8092
Brown, Mark and Windridge, David and Guillemaut, Jean-Yves (2017) A generalised framework for saliency-based point feature detection. Computer Vision and Image Understanding, 157 . pp. 117-137. ISSN 1077-3142
Brown, Mark and Guillemaut, Jean-Yves and Windridge, David (2014) A saliency-based framework for 2D-3D registration. In: VISAPP 2014: 9th International Conference on Computer Vision Theory and Applications, 05-08 Jan 2014, Lisbon, Portugal.