Welcome to The Centre for Multimodal AI
The Centre for Multimodal AI consolidates AI research in the School of Electronic Engineering and Computer Science. It builds on the expertise of world-leading academics in the school with emphasis on the development of Machine Learning algorithms, systems and applications for the Analysis and Synthesis of Multimodal Information such as Audio, Images, Videos, and Text, and on the development of AI methodologies in the domains of Games and Decision Support Systems.
The objective of the centre is to contribute to the development of AI methods and systems that will shape the future of our economy and society, striving not only for scientific excellence but also at setting and addressing research challenges for the benefit of our society. This includes challenges around developing AI methods and systems that are Trustworthy, Ethical and Responsible, but also efficient and capable of addressing some of the major challenges in the domains of Health, Education and Digital Economy.
The centre comprises more than 50 academics and 150 researchers, hosted across 6 research entities, namely the Centre for Digital Music, the Computer Vision group, the Multimedia and Vision group, the Computational Linguistics lab, the Game AI group, and the Machine Intelligence and Decision Systems group. Several members of the Centre are Fellows of The Alan Turing Institute and/or of the Digital Environment Research Institute (DERI).
Events
Recent Publications
- Designing Neural Synthesizers for Low-Latency Interaction
Caspe F, Shier J, Sandler M, Saitis C and McPherson A
Journal of The Audio Engineering Society, Audio Engineering Society vol. 73 (5), 240-255.
02-05-2025 - S 2 Reg: Structure-semantics collaborative point cloud registration
Xu Z, Gao X, Jiang X, Cheng S, Zhang Q and Li W
Pattern Recognition, Elsevier vol. 161
01-05-2025 - Assessing urban residents’ exposure to greenspace in daily travel from a dockless bike-sharing lens
Xu X, Wang J, Poslad S, Rui X, Zhang G, Fan Y and Yu G
International Journal of Applied Earth Observation and Geoinformation, Elsevier vol. 139
01-05-2025
Recent Grants
- (QM costs) ARCNET
Qianni Zhang
£15,496 Barts and the London Charity
01-03-2025 - 28-02-2026 - Knowledge transfer partnerships (KTP) 2024 to 2025 Rd2 - AstraZeneca
Greg Slabaugh and Michael Barnes
£283,459 Innovate UK
02-01-2025 - 01-07-2027 - (MDR-RA) Defining Clinical and Molecular Phenotypes of Multi-Drug Resistance in difficult to treat Rheumatoid Arthritis
Felice Rivellese, Shafaq Sikandar, Myles Lewis and Greg Slabaugh
£955,798 EU Commission - Horizon Europe
01-01-2025 - 31-12-2029