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We are developing the next generation of AI technologies, such as deep reinforcement learning algorithms, which will provide machines with fully automated strategies for complex interaction tasks with the world. We are increasingly working with advanced simulations and “digital twins” to optimise physical systems and their control algorithms at the design stage, whether in the automotive industry or industrial robotics.

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We are exploring the use of reinforcement learning and other AI technologies such as Bayesian Optimisation in computational settings rather than only physical systems. From our “automated neuroscientist” work to the potential automation of car crash simulations, we apply statistical machine learning solutions to important economic challenges.

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We are developing computer vision systems to assist machines to extract information from static images and streaming videos, and are exploring applications in manufacturing, security and other industries. In Medical Image Processing we work with several NHS Trusts, the Wellcome Trust, and commercial customers to develop techniques for diagnosis and decision support in X-Ray imaging and other modalities such as MRI and CT. These have the potential to reduce or prioritise Radiologist’s workloads, support training, and achieve better patient outcomes.

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Data Science

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Publications

Recent preprints can be found in arXiv. Below are some representative publications:

Research Content

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We're actively developing machine learning algorithms to model and manage large volumes of data – including high-dimensional and unstructured (images, networks and texts) and time-evolving data ­– to solve challenges for engineering, manufacturing and healthcare industry applications. Our research goes beyond data analytics, into decision support, automation and even fully autonomy.