Short Bio


alien-2010-partAdrian Clark has a background in physics and became involved in image processing and computer vision through electron microscopy in the dim and distant past. For about the last decade, the primary focus of his research has been in using machine learning to construct task-specific computer vision systems from generic components. He was a prime mover in the take-up of quantitative evaluation methods in vision. In his summer school talk, he will describe not only how performance can be measured but also explain how that can lead to insights into how to improve algorithms.
alien-2010-partDima Damen is a Lecturer in Computer Vision at the University of Bristol. She received her PhD from the University of Leeds (2009). Dima’s researcher interests are in the automatic understanding of object interactions, actions and activities using static and wearable visual (and depth) sensors. Dima is an associate editor of IET Computer Vision, co-chaired BMVC13, is an area chair for BMVC (2014-2017). In 2016, Dima was selected as a Nokia Research collaborator.
alien-2010-partKrystian Mikolajczyk did his undergraduate study at the University of Science and Technology (AGH) in Krakow, Poland. He completed his PhD degree at the Institute National Polytechnique de Grenoble, France, with an internship at the University of British Columbia , Canada. He then worked as a research assistant in INRIA, University of Oxford and Technical University of Darmstadt (Germany), before joining the University of Surrey as a Lecturer, and Imperial College London as a Reader in 2015. His main area of expertise is in image and video recognition, in particular in problems related to image representation and learning. He participated in a number of EU and UK projects in the area of image and video analysis. He published in top-tier computer vision, pattern recognition and machine learning forums. He has served in various roles at major international conferences co-chairing British Machine Vision Conference 2012 and IEEE International Conference on Advanced Video and Signal-Based Surveillance 2013. In 2014 he received Longuet-Higgins Prize awarded by the Technical Committee on Pattern Analysis and Machine Intelligence of the IEEE Computer Society.
Nicola Bellotto is a Reader in Computer Science at the University of Lincoln, and a member of the Lincoln Centre for Autonomous Systems (L-CAS). His research interests in autonomous systems range from mobile robotics to machine perception and intelligence, including active vision, sensor fusion, and qualitative spatial reasoning. Before joining Lincoln, he was a researcher in the Active Vision Lab at the University of Oxford. Nicola is a Principal Investigator in two EU H2020 projects and the recipient of a Google Faculty Research Award.
Nicolas Pugeault studied Engineering and Computer Science in Paris, did an MSc in Computational Intelligence at the University of Plymouth, and obtained a PhD in computer vision from the University of Goettingen in 2008. After graduating he has worked on a number of EU projects on cognitive vision and developmental robotics first at the University of Edinburgh, then the University of Southern Denmark and the Centre for Vision, Speech and Signal Processing (CVSSP) at Surrey. Since from the University of Goettingen in 2008. After graduating he has worked on a number of EU projects on cognitive vision and developmental robotics first at the University of Edinburgh, then the University of Southern Denmark and the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey. Since January 2016, he is a Lecturer in Computer Vision and Machine Learning with the University of Exeter. His research interests include cognitive systems, machine learning, and computer vision.
GrahamFinlaysonGraham Finlayson is the Director of the Colour Lab in the School of Computing Sciences at the University of East Anglia. Graham’s research spans colour image processing, physics-based computer vision and visual perception. He is interested in taking the creative spark of an idea, developing the underlying theory and algorithms and then implementing and commercialising the technology. Colour Lab IP ships in 100s of millions of products.
rdaviesRoy Davies is Emeritus Professor of Machine Vision at Royal Holloway, University of London. His interests include low-level vision, surveillance, vehicle guidance and crime detection. He has published more than 200 papers and three books – Electronics, Noise and Signal Recovery (1993), Image Processing for the Food Industry (2000), and Computer and Machine Vision: Theory, Algorithms, Practicalities (4th edition, 2012). Roy was awarded BMVA Distinguished Fellow in 2005 and Fellow of the International Association of Pattern Recognition in 2008.
kimTae-Kyun Kim is an Associate Professor and the leader of Computer Vision and Learning Lab at Imperial College London, UK. He obtained his PhD from Univ. of Cambridge in 2008 and Junior Research Fellowship in Cambridge for 2007-2010. His research interests primarily lie in decision forests (tree-structure classifiers) and linear methods for: articulated hand pose estimation, face recognition by image sets and videos, 6D object pose estimation, robot vision, activity recognition, object detection/tracking, which lead to novel active and interactive visual sensing.
tim_4Jun2011_smallTim Cootes completed a degree in Mathematics & Physics and then a PhD in Civil Engineering at Exeter. He moved to the University of Manchester in 1991 and has been there ever since, becoming a Professor of Computer Vision in 2006. His research focuses on statistical models of shape and appearance and their applications in computer vision and medical image analysis. He has published over 170 peer-review papers.
office_self_mainToby Breckon is currently a Reader (UK Associate Professor) within the School of Engineering and Computer Sciences, Durham University (UK). His key research interests lie in the domain of computer vision and image processing and he leads a range of research activity in this area. Dr. Breckon holds a PhD in informatics (computer vision) from the University of Edinburgh (UK). He has been a visiting member of faculty at the Ecole Supérieure des Technologies Industrielles Avancées (France), Northwestern Polytechnical University (China), Shanghai Jiao Tong University (China) and Waseda University (Japan). Dr. Breckon is a Chartered Engineer, Chartered Scientist and a Fellow of the British Computer Society. In addition, he is an Accredited Senior Imaging Scientist and Fellow of the Royal Photographic Society. He led the development of image-based automatic threat detection for the 2008 UK MoD Grand Challenge winners [R.J. Mitchell Trophy, (2008), IET Innovation Award (2009)]. His work is recognised as recipient of the Royal Photographic Society Selwyn Award for early-career contribution to imaging science (2011).
xieXianghua Xie is an Associate Professor at Swansea University. His research covers various aspects of computer vision and pattern recognition. He was a recipient of an RCUK academic fellowship. Some of his recent works include detecting abnormal patterns in complex visual and medical data, assisted diagnosis using automated image analysis, fully automated volumetric image segmentation, registration and motion analysis, and machine understanding of human interaction. He has published over 100 fully refereed research publications and (co-)edited several conference proceedings. He is an associate editor of IET Computer Vision and has chaired a number of conferences, including BMVC 2015.
jan koenderinkJan Koenderink is professor emeritus (in physics) from the University of Utrecht. He has worked in physics, mathematics, psychology, biology, philosophy and computer science. His main interests focus on the nature of awareness, especially for the case of vision. Much of his work is related to his interests in artistic expression.
neill campbellNeill Campbell is a Royal Society Industry Fellow and Lecturer (Assistant Professor) in Computer Vision, Graphics and Machine Learning at the University of Bath. He also holds an Honorary Lecturer position in the Virtual Environments and Computer Graphics Group in the Department of Computer Science at University College London where he was formerly a Research Associate working with Jan Kautz and Simon Prince. He completed his PhD, in the Computer Vision Group at the University of Cambridge, under the supervision of Roberto Cipolla and the guidance of George Vogiatzis and Carlos Hernández, funded by a Schiff Foundation Scholarship and Toshiba Research. His main area of research involves learning generative models of shape (2D and 3D) and appearance from images.
bob fisherRobert Fisher, FIAPR, FBMVA received a BS (Mathematics, California Institute of Technology, 1974), MS (Computer Science, Stanford, 1978) and a PhD (Edinburgh, 1987). Since then, Bob has been an academic at Edinburgh University, a full Professor since 2003, including a stint as of Dean of Research in the College of Science and Engineering. He has been the Education Committee chair and is currently the Industrial Liaison Committee chair for the Int. Association for Pattern Recognition. His research covers topics in high level computer vision and 3D and 3D video analysis, focussing on reconstructing geometric models from existing examples, which contributed to a spin-off company, Dimensional Imaging. He has developed several on-line computer vision resources, with over 1 million hits. Most recently, he has been the coordinator of EC projects 1) acquiring and analysing video data of 1.4 billion fish from over about 20 camera-years of undersea video of tropical coral reefs and 2) developing a robot hedge-trimmer. He is a Fellow of the Int. Association for Pattern Recognition (2008) and the British Machine Vision Association (2010).
marta betckeMarta Betcke is a lecturer in Department of Computer Science and UCL. She is a member the Centre for Medical Image Computing and one of the founding members of the Centre for Inverse Problems at UCL. After obtaining PhD in Numerical Analysis in 2007, Betcke was a postdoc at the University of Manchester where she developed a new class of reconstruction methods, multi-sheet surface rebinning methods, for axially offset gantry cone beam CT scanners. Between 2010-2013 she held an EPSRC Postdoctoral Fellowship “Image reconstruction: the sparse way” which initiated a shift of Betcke’s research towards variational methods for image reconstruction from compressed/subsampled measurements in various tomographic applications including X-ray transmission, scatter and photoacoustic tomography with the ultimate goal of enabling solution of dynamic inverse problems. Recently, she also developed interest in machine learning informed approaches to inverse problems.