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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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understand where stars form, how stellar feedback changes their surroundings, and how matter moves through galaxies over time shaping them. Most of my research uses large astronomical data sets across
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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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, and interpretability of quantum-inspired models against classical machine learning methods. Develop a prototype system integrated with learning management system (LMS) data (e.g., Moodle) to demonstrate
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is carried out within the LHCb collaboration that runs one of the four large experiments at the Large Hadron Collider at CERN as well as towards future collider developments. I supervise a number of
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large scale training data available.
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The Research Database Manager plays a key role in supporting the Faculty’s education and research activities through the development, management, and effective use of commercial data platforms. These resources
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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