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On their own, traffic accidents cause 1.3 million fatalities every year – and improper situational awareness is often a major cause. This project aims to exploit big spatio-temporal data to design
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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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The proliferation of misinformation and disinformation on online platforms has become a critical societal issue. The rapid spread of false information poses significant threats to public discourse
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Automating code generation, SQL query formulation, and data preprocessing pipelines is a crucial step toward intelligent and efficient software development. This project aims to leverage large
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large scale training data available.
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As education systems increasingly adopt AI to support teaching and learning, the automation of assessment and feedback processes has emerged as a critical area of innovation. Large-scale learning
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, and costs of running diverse applications in large-scale distributed systems. This project offers researchers and students a chance to explore cutting-edge concepts in AI-driven infrastructure
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The primary objective of this project is to enhance Large Language Models (LLMs) by incorporating software knowledge documentation. Our approach involves utilizing existing LLMs and refining them
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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are computationally expensive for modern large models. Incomplete Uncertainty Modeling: Most methods focus on single-modal data and fail to account for uncertainty arising from multi-view or multimodal interactions