About us

The Centre carries out sustainable research in artificial intelligence (AI), data analytics and modelling; focusing on data-driven AI systems that are resilient, robust, trustworthy and adaptable to changing operational conditions.

The research develops the new mathematical and computational frameworks and tools that helps design the new generation of AI systems. These can be used in a wide range of applications, including health technology, security, social sciences and space and earth observation.

The Centre  delivers high impact and inclusive research supported by extensive collaboration with a network of industrial partners, Leicester NIHR Biomedical Research Centre, Institute for Precision Health, Health Data Research UK, and Space Park Leicester’s £13 million METEOR programme. The Centre supports externally funded research projects from departments across the University, including Mathematical Sciences, Computing, Cardiovascular Sciences, and Archaeology and Ancient History.

Leadership Team

• Professor Alexander Gorban – Director (AI, Data Analytics and Modelling)
• Professor Ivan Tyukin – Deputy Director (Provably Resilient, Robust and Trustworthy AI)
• Dr Alistair McEwan (Software Engineering and Verification)
• Professor Salman Siddiqui (Biomedical Research Centre Interface)
• Professor Thomas Yates (Diabetes Research Centre Interface)
• Professor Tim Coats (Life Sciences Interface)
• Professor Liu Lu (Fault Tolerant AI Systems)

Partnerships

We work with a number of academic, public, and industrial partners on a broad range of theoretical and practical challenges around AI, Data Analytics, Machine Learning, and Modelling.

Our vision

• AIDAM research in AI, Data Analytics and Modelling is focused on Resilient, Robust, and Trustworthy data-driven AI systems.
• Collaboration across disciplines with experts from the various departments and schools in AIDAM is imperative for bringing Leicester to the forefront of research in AI and Data Analytics.
• Development of methods needs data. Analysis of data needs methods. If we properly select, adapt and professionally apply these methods, the data tell us a fascinating story.
• Development of new methods and analysis of data collections by many methods are two main mutually supportive directions of AIDAM activity.