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Field
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of peatlands under future climate change, incorporating projected outcomes from restoration activities and the identification of environmental tipping points from mechanistic modelling of species distributions
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
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persists, even for the most powerful sensors operating in this way. A drastic departure from this sensing architecture is “multistatic” radar – enacted by a coherent network of spatially distributed sensors
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The Mediator of Replication Checkpoint Mrc1 (in yeast) and Claspin (in mammals) are central regulators of DNA replication. Our recent work has shown how these factors also ensure the symmetric distribution
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outcomes. By mapping these gene distributions and integrating them into a predictive tool, the project seeks to stratify patients as likely responders or non-responders to chemotherapy, enabling personalised
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Project summary: A transition to net zero is desirable overall, but its costs and benefits are unevenly distributed across time, space, and between individuals, and policy to implement it must be
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal
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or 3-dimensional spaces, enabling insights about the underlying structure and distribution of the data. However, due to the heavy data compression into a space with only 2 or 3 degrees of freedom
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relationship between brain structure, myelin distribution and genetic factors in MS. Research Focus: Recently, computational pipelines have been developed to integrate genetic and imaging databases