Knowledgeable and truly inspiring educator.
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Professor Hubert Shum is a Professor of Visual Computing and the Director of Research in the Department of Computer Science at Durham University. His research focuses on modelling spatio-temporal information using responsible AI, with key interests in responsible AI, computer vision, computer graphics, and AI in healthcare. These efforts have applications in healthcare, space technology, art, autonomous vehicles, and robotics. Shum holds additional appointments at Durham University as Fellow of the Wolfson Research Institute for Health and Wellbeing, Co-Founder and Co-Director of the Durham University Space Research Centre, Steering Group Member of the Centre for Visual Arts and Culture, and Advisory Board Member of the TORUS EPSRC project supporting Parkinson's disease patients with sensing technologies.
Shum has supervised more than 30 PhD students, recruited multiple postdoctoral researchers, and collaborated with international researchers from the UK, France, China, Japan, and India. He has led research as Principal Investigator on projects funded by EPSRC, the Ministry of Defence, the Royal Society, and Innovate UK, and serves as Co-Investigator on the £4.17 million NortHFutures EPSRC project establishing a digital health hub in North East England. His accolades include Exceptional Achievement for Excellence in PhD Supervision (Durham University, 2023), Exceptional Achievement for Excellence in Teaching (2022), Sullivan Doctoral Thesis Prize runner-up, Best Paper Award at IEEE/CVF CVPR DCAMI Workshop (2024), Best Paper Award at IEEE International Conference on Human-Machine Systems (2021), Best Student Paper Award at GRAPP (2020), Best Poster Awards at ACM SIGGRAPH MIG (2019, 2016), and Best Paper Award at ACE (2017). Shum contributes to the academic community as a member of the EPSRC Peer Review College, Associate Editor of Computer Graphics Forum (2019–2023), Guest Editor of International Journal of Computer Vision (2020 Special Issue on Machine Vision and Deep Learning), and Program Committee member for over 20 conferences including Eurographics and Pacific Graphics. He has authored over 200 research publications. Notable recent works include "RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation" (ECCV 2024, Oral Paper), "MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment" (ECCV 2024, Oral Paper), "Multi-Task Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising" (IEEE TVCG, 2024), "Adaptive Graph Learning from Spatial Information for Surgical Workflow Anticipation" (IEEE TMB, 2025), and "HINT: High-quality INpainting Transformer with Mask-Aware Encoding and Enhanced Attention" (IEEE TMM, 2024).
