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About

Angus Addlesee is a researcher specializing in conversational AI, social robotics, and spoken dialogue systems, with a particular focus on deploying intelligent robots in real-world healthcare and public settings. His work sits at the intersection of large language models (LLMs), multimodal interaction, and human-robot communication, tackling the complex challenge of enabling robots to hold natural, multi-party conversations with multiple people simultaneously. Addlesee's most influential contribution — "A Multi-party Conversational Social Robot Using LLMs" (2024, 22 citations) — demonstrates a fully integrated LLM-based dialogue system embodied in a social robot, marking a significant step toward deployable conversational agents. His closely related work on robot assistants in hospital memory clinics (12 citations) highlights a meaningful real-world application, where robots support conversations between patients, companions, and clinical staff. Earlier work on visually-aware robot receptionists (2022) further underscores his commitment to perceptually grounded interaction. A recurring theme across Addlesee's research is advocacy for thoughtful design: his 2025 paper argues for early-stage collaboration between roboticists and speech researchers to build robots genuinely suited for audio interaction. His contributions are shaping how conversational robots can meaningfully serve vulnerable populations, including elderly patients in gerontological care.