Encourages questions and exploration.
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Professor David Suter is a Professor of Computer Science in the School of Science (Computing and Security) at Edith Cowan University. He holds a Doctor of Philosophy from La Trobe University, awarded in 1991. His distinguished career spans multiple institutions, including his current role as (Research) Professor of Computer Science at Edith Cowan University since January 2018, (Adjunct) Professor of Computer Science at the University of Adelaide since December 2017, Professor of Computer Science at the University of Adelaide from 2008 to 2017, Professor of Electrical and Computer Systems Engineering at Monash University from 2006 to 2008, Associate Professor of Electrical and Computer Systems Engineering at Monash University from 2002 to 2006, Senior Lecturer in Electrical and Computer Systems Engineering at Monash University from 1992 to 2002, and Lecturer in Computer Science and Computer Engineering at La Trobe University from 1988 to 1992.
Professor Suter's research specializations include computer vision with a focus on robot vision, image processing, pattern recognition, big-data analysis, robust statistics, and computational geometry. He has made significant contributions through editorial roles on boards of leading journals such as the International Journal of Computer Vision (Honorary Editorial Board, formerly 2004–2013), Pattern Recognition (since August 2017), IPSJ Transactions on Computer Vision and Applications (2008–2013), Journal of Mathematical Imaging and Vision (2007–2010), and Machine Vision and Applications (2006–2008). He served as a Member of the Australian Research Council College of Experts from 2008 to 2011. Key publications encompass recent works like "Automated abdominal aortic calcification scores and atherosclerotic cardiovascular disease in the UK Biobank Imaging Study" (Journal of the American College of Cardiology: Advances, 2026), "PanoSCU: A Dataset for Panoramic Indoor Scene Understanding" (IEEE Access, 2025), and highly cited papers such as "As-projective-as-possible image stitching with moving DLT" (Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2013). His research has attracted major grants, including Australian Research Council Discovery Projects and National Health and Medical Research Council Ideas Grants, influencing advancements in computer vision, machine learning, and medical imaging.
