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on this technology for its automated warehouses and fulfilment centres. The aim of this project is to use discrete optimisation techniques (e.g. Integer Programming) to design new algorithms for MAPF. An example
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the Law Enforcement (LE) context. In this project we aim to improve law enforcement’s understanding of online criminal communications, exploring texts for automated understanding of intent, sentiment
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following failures of command or task execution by robots [Baker, 2018, Esterwood 2022, Park 2023], little work has been done to estimate the effects of direct disobedience on human-robot trust and joined
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data
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while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
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Machine learning, dynamical systems theory, control theory, signal processing, network theory, neuroscience are all relevant and a student should have strong knowledge in at least one of these and a
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Explainability and Compact representation of K-MDPs Creating a 21st Century Helpline for Enhanced Support and Continuity of Care Formally Verified Automated Reasoning in Non-Classical Logics Efficient CEGAR
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will study the development, adoption, and implications of digital technology and insurance—such as tools for capturing individualised data about behavioural risk factors and automating enforcement
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interactions. In this research, you need to understand how spins interact with their environment and how to read-out and control single spins. This requires understanding of concepts like atom optics, magnetic
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nanomaterials" (with Prof Nikhil Medhekar) "Ultrafast charge dynamics in photoactive materials" "Artificial-intelligence-controlled atom-by-atom synthesis of functional organic nanomaterials" web page For further