The Visual Artificial Intelligence Laboratory was founded in 2012 by Professor Cuzzolin, under the name of 'Machine Learning' (and later 'Artificial Intelligence and Vision') research group, and has since been conducting work at the boundaries of human action recognition in computer vision. Prof Cuzzolin is a leading scientist in the mathematics of uncertainty, in particular random set and belief function theory. The team's interests have since expanded towards machine learning and Artificial General Intelligence, robotics, in particular surgical robotics and autonomous driving, as well as AI for Healthcare. Our research interests span a number of frontier topics in: - artificial intelligence (epistemic AI and machine theory of mind, but also neurosymbolic AI) - computer vision (action and activity detection, future event prediction, video captioning and scene understanding) - machine learning (continual learning, federated learning, self-supervision and metric learning) - robotics (with a focus on surgical robotics), autonomous driving (the detection of road events for situation awareness) - AI for healthcare (the monitoring of people in care homes, the early diagnosis of dementia, empathetic healthcare via theory of mind). - uncertainty theory (random set and belief functions). The Lab currently runs on a budget of around £3.2M (not fully incorporating the €4.3M Horizon 2020 project SARAS or the €3M FET Epistemic AI we are coordinating), with currently nine live projects funded by Horizon 2020, the Leverhulme Trust, Innovate UK, Huawei Technologies, UKIERI, and the School of Engineering, Computing and Mathematics. The budget is projected to further significantly increase in 2022. The group has built a leadership position in the field of deep learning for action detection, and is currently pushing to reshape the foundations of artificial intelligence to better incorporate and model second-order, 'epistemic' uncertainty: a concept we call "epistemic AI".