Visualisation
We focus on unlocking the power of visualisation to enhance cognition, integrate intelligence, and facilitate decision making.
The realisation of artificial intelligence requires the integration of machine intelligence and human intelligence. Visualisation uses interactive visual representations of data to enhance cognition by leveraging the perceptual abilities of human eyes. In the era of big data, it plays a crucial role in making sense of vast amounts of complex information. Visual analytics leverages visualisation techniques and interfaces to create an immersive analytical environment, which enables utilising visual understanding and machine understanding as complementary means to combine human and machine intelligence. In human-centered analysis and decision-making scenarios, such as security, military, disaster prevention and mitigation, interactive and intelligent visual analysis will become a core analytical mode.
Aims
- Profound research in visualisation techniques and visual analytics
- Interdisciplinary applications of visualisation and visual analytics
Research
General visualisation techniques
- Computer Graphics
- Animation and rendering
- Image and signal processing
- Geometric design, modelling and processing
- AR/VR/immersive displays
Mathematical foundations and machine learning algorithms
- Data clustering and aggregation
- Dimensionality reduction
- Feature detection, extraction, tracking and transformation
- Machine learning techniques
- Numerical methods
Application areas for visualisation and visual analytics
- Machine Learning
- Health and Medicine
- Engineering and Robotics
- Social Science
Current projects
- Uncovering the “instincts” of deep generative models for fair and unbiased visual content creation. Funding approximately £72,922. EPSRC Doctoral Training Partnerships.
Meet the team
Events
Seminars from members and visitors are presented at the visual computing research seminar series.
Publications
- Yang, W. et al., 2024. Interactive reweighting for mitigating label quality issues. IEEE Transactions on Visualization and Computer Graphics 30 (3), pp.1837-1852. (10.1109/TVCG.2023.3345340)
- Huang, Z. et al., 2024. SpeechMirror: A multimodal visual analytics system for personalized reflection of online public speaking effectiveness. IEEE Transactions on Visualization and Computer Graphics 30 (1), pp.606-616. (10.1109/TVCG.2023.3326932)
- Chen, C. et al., 2023. A unified interactive model evaluation for classification, object detection, and instance segmentation in computer vision. Presented at: IEEE VIS 2023 Melbourne, Australia 22-27 October 2023. Institute of Electrical and Electronics Engineers(10.1109/TVCG.2023.3326588)
- Song, S. et al. 2023. Feature proliferation — the "cancer" in StyleGAN and its treatments. Presented at: International Conference on Computer Vision (ICCV) 2023 Paris, France October 1 - 6, 2023. Proceedings of IEEE/CVF International Conference on Computer Vision. IEEE. , pp.2360-2370. (10.1109/ICCV51070.2023.00224)
- Deng, Z. et al. 2023. Sketch2PQ: freeform planar quadrilateral mesh design via a single sketch. IEEE Transactions on Visualization and Computer Graphics 29 (9), pp.3826-3839. (10.1109/TVCG.2022.3170853)
- Xia, J. et al., 2023. Interactive visual cluster analysis by contrastive dimensionality reduction. IEEE Transactions on Visualization and Computer Graphics 29 (1), pp.734-744. (10.1109/TVCG.2022.3209423)
- Li, Z. et al., 2022. A unified understanding of deep NLP models for text classification. IEEE Transactions on Visualization and Computer Graphics 28 (12), pp.4980-4994. (10.1109/TVCG.2022.3184186)
- Grange, J. A. et al. 2022. XAI & I: Self-explanatory AI facilitating mutual understanding between AI and human experts. Presented at: 26th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2022) 7-9 September 2022. Elsevier(10.1016/j.procs.2022.09.419)
- Chen, C. et al., 2022. Towards better caption supervision for object detection. IEEE Transactions on Visualization and Computer Graphics 28 (4), pp.1941-1954. (10.1109/TVCG.2021.3138933)
- Maher, K. et al., 2022. E-ffective: a visual analytic system for exploring the emotion andeffectiveness of inspirational speeches. IEEE Transactions on Visualization and Computer Graphics 28 (1), pp.508-517. (10.1109/TVCG.2021.3114789)
- Liang, Y. et al. 2022. Exploring and exploiting hubness priors for high-quality GAN latent sampling. Presented at: The 39th International Conference on Machine Learning (ICML 2022) Baltimore, Maryland USA 17-23 July 2022. Vol. 162.
- Chen, C. et al., 2021. Interactive graph construction for graph-based semi-supervised learning. IEEE Transactions on Visualization and Computer Graphics 27 (9), pp.3701-3716. (10.1109/TVCG.2021.3084694)
- Cao, K. et al., 2021. Analyzing the noise robustness of deep neural networks. IEEE Transactions on Visualization and Computer Graphics 27 (7), pp.3289-3304. (10.1109/TVCG.2020.2969185)
- Pan, Y. et al., 2019. InSocialNet: Interactive visual analytics for role-event videos. Computational Visual Media 5 (4), pp.375-390. (10.1007/s41095-019-0157-9)
- Zhang, J. et al., 2019. Accelerating ADMM for efficient simulation and optimization. ACM Transactions on Graphics 38 (6) 163. (10.1145/3355089.3356491)
- Xiang, S. et al., 2019. Interactive correction of mislabeled training data. Presented at: IEEE VIS 2019 Vancouver, BC, Canada 20-25 October 2019. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE(10.1109/VAST47406.2019.8986943)
- Zhang, J. et al., 2019. Static/dynamic filtering for mesh geometry. IEEE Transactions on Visualization and Computer Graphics 25 (4), pp.1774-1787. (10.1109/TVCG.2018.2816926)
- Liu, S. et al., 2018. Visual diagnosis of tree boosting methods. IEEE Transactions on Visualization and Computer Graphics 24 (1), pp.163-173. (10.1109/TVCG.2017.2744378)
Next steps
Research that matters
Our research makes a difference to people’s lives as we work across disciplines to tackle major challenges facing society, the economy and our environment.
Postgraduate research
Our research degrees give the opportunity to investigate a specific topic in depth among field-leading researchers.
Our research impact
Our research case studies highlight some of the areas where we deliver positive research impact.