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Associate Professor David Suter

Personal Details
Affiliation: Department of Electrical and Computer Systems Engineering, Faculty of Engineering / Centre for Intelligent Robotics Research Monash University, Australia http://www.ds.eng.monash.edu.au/dpl/suter_research/index.htm
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Biography
Dr Suter is an Associate Editor of the International Journal of Computer Vision, and has also chaired major international conferences ? e.g., Asian Conference on Computer Vision 2002). He also maintains strong active international contacts, including ARC funded collaborations with leading Statisticians in Australia and Switzerland (EPFL and University of Geneva); leading computer vision researchers in Australia, Japan (Okayama University and Nagoya) and France (La Rochelle and IRISA). He is also on the editorial board of another international journal and is Vice-President of the Australian Pattern Recognition Society. Dr Suter has established an active and vibrant laboratory and associate research group (Digital Perception Laboratory), has led a team to establish as cross-faculty visualization laboratory (Vizlab), and another team to establish an Institute for Computer Vision Systems Engineering. He is also part of the Centre for Perceptive and Intelligent Machines in Complex Environments. He has secured numerous grants as lead CI and has also been recognized by being one of the CI?s of an ARC supported research center. ARC support over the full years of postdoctoral career (1992-present) firmly establishes him as a leading and innovative researcher of national and international standing. His success and commendation for postgraduate supervision attests to his ability to foster high quality research by new entrants into the area.
Areas of Expertise
Research: Main expertise is in fundamental understanding and technology in low level vision (underpins most visual tasks) particularly in motion estimation and related areas (e.g., tracking). A second strong area of expertise is in robust statistical methods. Amongst the participants, the participant is unique in these strengths. The strengths are fundamental to a large cross-section of the proposed activities so the expertise of this participant is likely to be very complementary and in large demand.
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