AIiH 2024 will have up to 5 Keynote speakers.

Yulan He, Kings College London

Tentative title: “Advancements in Pharmacovigilance and Radiology with Large Language Models

Yulan He is a Professor in Natural Language Processing (NLP) at the Department of Informatics in King’s College London, UK. She is currently holding a prestigious 5-year UKRI Turing AI Fellowship. Yulan’s research interests lie in the integration of machine learning and NLP for language understanding. She has published over 200 papers on topics including model interpretability, machine reading comprehension, rumour veracity assessment, and biomedical text mining. She has received several prizes and awards for her research, including a SWSA Ten-Year Award, a CIKM Test-of-Time Award, and AI 2020 Most Influential Scholar Honourable Mention. She served as the General Chair for AACL-IJCNLP 2022 and a Program Co-Chair for EMNLP 2020.

Timothy Rittman, Cambridge University

Keynote Title: “AI as the future of memory clinics: hype or happening?

Timothy Rittman is a Senior Clinical Research Associate at the University of Cambridge where he studies neurodegenerative disorders, combining neuroimaging, cognitive assessments and neuropathology to understand how these diseases progress through the brain. He has a particular interest in translating methods from artificial intelligence and big data for use in memory clinics. Tim co-leads the DEMON dementia network’s Imaging Working group and is an adviser to the World Young Leaders in Dementia. He is an Honorary Consultant Neurologist at Addenbrookes hospital, as a consultant in the Addenbrookes Memory Clinic, leading a clinic for people with Progressive Supranclear Palsy and Corticobasal Degeneration, and co-leading a dementia genetics clinic.

Konstantinos Kamnitsas, Oxford University

Konstantinos Kamnitsas is Associate Professor of Engineering Science (Biomedical Imaging) at the Department of Engineering Science, and a Non-Tutorial Fellow at Wolfson College. His research focuses on Machine-Learning (ML) and primarily deep neural networks for medical image analysis. His work has two main goals: Develop more reliable, transparent and accountable models for safer use in healthcare.
Empower radiologists, clinicians and researchers with intelligent ML-based tools to better address their research questions and needs of clinical workflows.
Konstantinos completed his PhD in 2019 at Imperial College London, where he developed some of the first 3-dimensional neural networks for processing volumetric medical data, such as MRI and CT, and methods for improving generalization to heterogeneous data. His work has won various awards, among which two international competitions for brain cancer and ischemic stroke lesion segmentation. He also obtained an MSc in Computing Science in 2013, also from Imperial College, and the diploma in Electrical and Computer Engineering in 2010 from Aristotle University of Thessaloniki, Greece. He has also spent time conducting research in industry, such as at the Healthcare Intelligence team of Microsoft Research and Kheiron Medical Technologies. He became a Lecturer in 2021 at the School of Computer Science of the University of Birmingham, where he retains a position as an Honorary Research Fellow since 2022, when he joined the University of Oxford as an Associate Professor. He is member of the Editorial Board of Medical Image Analysis, one of the field’s leading journals.

Jacques Fleuriot, Edinburgh University

Jacques Fleuriot is a full Professor in the School of Informatics and hold a Chair of Artificial Intelligence. He is head of the AI Modelling Lab (AIML), within the Artificial Intelligence and its Applications Institute (AIAI), Academic Lead and a member of the core management team for the University of Edinburgh’s £20m Advanced Care Research Centre (ACRC). As part of the ACRC, Jacques lead the Integrated Technologies of Care research theme. He is the AI Lead on the NIHR Grant, Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC), and he is member of the Strategic Opportunities and Futures Board of the newly created University of Edinburgh’s £7.5m Centre for Investing Innovation. His main field of research lies in AI Modelling, which spans areas such as interactive theorem proving, formal verification, process modelling, and AI/machine learning applied to health/care, medicine and other complex domains.