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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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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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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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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
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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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understand our place in the cosmos. I am a member of most large stellar spectroscopic surveys (e.g., Gaia, SDSS-V, 4MOST, GALAH, Gaia-ESO), providing access to pan-optic data across all visible and infrared
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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I work on a wide range of topics with my local group and in collaboration with members of three large international collaborations. The central focus of my research is to understand how the observed
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up