Research & Innovation
Context
LIDA’s vision for Research and Innovation (R&I) is to leverage data science and AI in addressing societal, health and environmental grand challenges. To do this, we bring together applied research groups and data scientists from disciplines across the university to conduct inter-disciplinary research and develop, apply and evaluate data-driven approaches to science.
Our R&I activity is led by academics from across Faculty Schools and Institutes, and via our Communities and Programmes (C&Ps). These special interest groups bring together methodologists, applied researchers and external partners to tackle grand challenges in data-driven science and AI.
New to this academic year is our Food community – bringing together experts and research clusters across the university to deploy data science and AI to tackle food system challenges – and Science and Data Science programme – a group exploring how scientific theory, methods and practice are shifting in light of new technology and methods.
We have plans in place to grow our C&P activity and formalise how C&Ps operate (more on this to follow this academic year!). We are also currently streamlining and refreshing our special interest research groups, which bring together researchers from across the University to work on dedicated methodological and applied agendas in data-driven science.
Partnerships and Collaborations
A key mechanism through which we aim to support academics is our national and local partnerships. We have a sustained record of collaboration with Alan Turing Institute the N8 Research Partnership and, especially through our Health Community, Bradford Institute for Health Research (BIHR) and University of York.
These partnerships have been pivotal to securing research funding: the NPCC-funded Policing Centre of Excellence, for example, is a collaboration between data-oriented Criminologists at University of Leeds and York; NIHR PHIRST REACH builds on expertise in data-driven health evaluation shared between Leeds, York and BIHR and the MRC-funded Biomedical Data Science and Careers Leadership group, a collaboration with several N8 universities and industry partners.
AI is clearly transforming the research landscape, presenting opportunities for new collaboration. An example of this emerging funding landscape: Nick Watson, who co-leads our LIDA Food, has recently been funded by the Bezos Earth Fund, to develop an AI Platform for Sustainable Protein from Agri-Food Waste.
To capitalise on the opportunities around AI, we’ve been working across faculties on bringing the AI Research Community together. LIDA AI is now a network of ~300 academics working on or with AI. We hosted an inaugural AI Research at Leeds event in July and will be following up with a sandpit series early in the new year.
Achievements
Over the last 12 months, LIDA has been involved in 83 grant projects valued at £113.5m. 94% of these projects are supported via LASER, LIDA’s secure data platform. LASER is therefore an essential service for applied data science and AI at the university.
The recently launched Healthy & Sustainable Places Data Service (HASP), for example, involves collecting data from industry and government partners, to enable secure access to data describing place-based population outcomes and behaviours. Also worth emphasising is the Wellcome-funded Suicide: An International Social Justice Study, led by Prof Sarah Waters (School of Languages, Cultures & Societies), involving highly sensitive individual-level data, administered via LASER.
In March 2025, we launched our first LIDA Academic Fellowship role: a two-year position supporting an academic to help advance and set out an agenda for impactful data science and AI research within LIDA’s challenge areas. Owen Johnson is the first of these Fellows. Owen has an international reputation for his leadership role in process-oriented data science in healthcare and his project explores process mining as a framework improving UK health and social care pathways.
Process mining has been widely adopted in many industries but the UK has been a slow adopter, particularly in healthcare where the complexity of care demands novel approaches. In previous work we have been able to demonstrate how process data can be used to improve the prediction and better management of patient care but there is more to be done – both in solving adoption challenges like data quality and research integrating AI methods and evaluating AI based interventions. The project aligns closely to the new NHS 10 year plan and will help NHS address waiting lists, bottlenecks and the shift from hospital care to communities.
Owen Johnson
LIDA Academic Fellow
As well as running several CPD courses on process mining, attended by NHS and industry analysts in the healthcare domain, he has secured funding for developing regional case studies, a single national Body of Knowledge for process mining implementation in the NHS and for organising an international workshop, hosted at Leeds, in Spring 2026.
By Dr Roger Beecham
LIDA Director of Research & Innovation
Find out more about LIDA Research & Innovation Return to the Annual Showcase 2025