Maria Liakata is Professor of NLP at the School of Electronic Engineering and Computer Science, Queen Mary University of London. She holds a UKRI/EPSRC Turing AI fellowship (2019-2025) on Creating time sensitive sensors from user-generated language and heterogeneous content. The research in this fellowship involves developing new methods for NLP and multi-modal data to allow the creation of longitudinal personalized language monitoring. She has also led projects on language sensing for dementia monitoring & diagnosis, opinion summarisation, and rumour verification from social media. At the Alan Turing Institute she founded and co-leads the NLP and data science for mental health special interest groups. She has published over 180 papers on topics including semantics, summarisation, rumour verification, opinion mining, resources and evaluation and biomedical NLP. She is the PI of the newly funded UKRI/RAi UK Keystone project on Addressing Sociotechnical Limitations of Large Language Models (AdSoLve).

MultimodalAI'24 Keynote Title: Longitudinal language processing for dementia

MultimodalAI'24 Keynote Abstract: While the advent of Large Language Modes (LLMs) has brought great promise to the field of AI there are many unresolved challenges especially around appropriate generation, temporal robustness, temporal and other reasoning and privacy concerns especially when working with sensitive content such as mental health data. The programme of work I have been leading consists in three core research directions: (1) data representation and generation (2) methods for personalised longitudinal models and temporal understanding (3) evaluation in real-world settings, with a focus on mental health. I will give an overview of work within my group on these topics and focus on work on longitudinal monitoring for dementia.