This talk imagines a future where information systems interactions go beyond static interfaces and evolve into dynamic conversations tailored to individual users. Immersive personalisation in conversational informationseeking represents a paradigm shift, redefining how we search, explore, and engage with knowledge. Traditionally, users interact with documents as discrete units of information. However, research in conversational systems has suggested that users rarely think in terms of “documents”. Instead, they focus on fulfilling their information needs, often shaped by specific goals, contexts, and personal preferences. Fuelled by the advances with large language models, immersive personalisation takes this even further, harnessing adaptive interfaces to build systems that intuitively anticipate and adapt to what users want when they want it.
Biography: Her work focuses on developing next-generation capabilities for intelligent systems, including spoken
Trippas is particularly interested in how conversational systems can revolutionise information seeking, especially through generative interactive information retrieval and novel interfaces beyond traditional text search. She has extensive experience analysing human informationseeking behaviour and developing novel approaches to personalised intelligent assistance, data-driven modelling, and profiling human behaviours. Trippas employs many research methods and consistently adopts user-centric data capture and analysis approaches, focusing on modelling and profiling human behaviours. Additionally, she is a member of the NIST TREC program committee, ACM CHIIR steering committee member, and SIGIR Artifact Evaluation Committee Vice-chair. Trippas serves on numerous information retrieval events, such as SWRIL’25’, resource & reproducibility chair (ACM SIGIR’25), workshop chair (ACM CHIIR’25), and technical program chair (ACM CHIIR’26).