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This research project focuses on advancing Artificial Intelligence for text simplification, to prioritise user-centred accessibility and pragmatic fidelity. Digital information is often locked behind complex language. This can have devastating consequences in domains like healthcare, education, and public services. My work explores how AI can bridge between expert language and public understanding, ensuring essential meaning is not lost.

I am developing context-sensitive AI models that are trained to simplify texts while retaining their original communicative intent, nuance, and coherence. This involves drawing on theories from experimental pragmatics, such as Relevance Theory and Grice's maxims, to guide the AI in identifying and appropriately clarifying implicit language, presuppositions, and context. The goal is to design adaptive systems that meet diverse linguistic and cognitive needs, offering a model for how future AI can be co-designed with accessibility as a core principle.

I am a Leverhulme Trust Doctoral Scholar, supported by the Leverhulme Trust's funding for my research.