AI Colloquium with Prof. Allan Tucker on “Lessons from Synthetic Health Data Generation: Fidelity, Privacy, Augmentation & Time”

On Wednesday, February 4, 2026, Prof. Allan Tucker from Brunel University London will hold a presentation on “Lessons from Synthetic Health Data Generation: Fidelity, Privacy, Augmentation & Time” as part of the AI Colloquium series.

About the AI Colloquium

The AI Colloquium, organized by the Lamarr Institute, the Research Center Trustworthy Data Science and Security (RC Trust) and the Center for Data Science & Simulation at TU Dortmund University (DoDas), provides a platform for leading researchers to present groundbreaking work in the field of Machine Learning and Artificial Intelligence. These 90-minute sessions, unlike other colloquia, focus on interactive dialog and international collaboration and include one-hour lectures and 30-minute Q&A sessions. The colloquium will be held mainly in English. The hybrid format of the colloquium ensures that all interested parties can participate either in person or online via Zoom.

About the Talk

Primary healthcare data is vital to research, yet due to its personal nature, it is frequently associated with privacy concerns. A possible solution to this issue may be the usage of synthetic data. A long-term collaborative project between Brunel University London and the UK Medicine and Health Regulatory Authority aims at uncovering its potential and found the main issue with synthetic data to be its inherent bias.
Prof. Tucker will evaluate the project by elaborating on the generation of synthetic data and the detection of bias. He will present ways toward a more accurate representation of the actual UK population as well as methods to deal with concept drift amid shifts in data.

About the Speaker

Allan Tucker is Professor of Artificial Intelligence in the Department of Computer Science at Brunel University London, where he heads the Intelligent Data Analysis Group. He has been researching Artificial Intelligence and Data Analysis for 28 years. His research work includes long-term projects with Moorfields Eye Hospital where he has been developing pseudo-time models of eye disease and with DEFRA on modelling fish population dynamics using state space and Bayesian techniques. Currently, he has projects with Google, the University of Pavia Italy, the Royal Free Hospital, UCL, Zoological Society of London and the Royal Botanical Gardens at Kew. He is currently CI on a Centre of Excellence for Regulatory Sciences and Innovation. He serves regularly on the PC of the top AI conferences (including IJCAI, AAAI, and ECML) and is on the editorial board for the Journal of Biomedical Informatics. He has been widely consulted on the ethical and practical implications of AI in health and medical research by the NHS, and the use of machine learning for modelling fisheries data by numerous government thinktanks and academia.