15 new smart data research fellowships
Announcing our Fellows
Smart Data Research UK (SDR UK) is funding 15 new Fellowships which address some of the UK’s most pressing challenges, from combating AI-generated misinformation to forecasting demand for electric vehicle charging infrastructure. The Fellowship projects, each worth up to £200,000, cover SDR UK’s four research themes: productivity and prosperity, health and wellbeing, digital society, and sustainability. All projects will start in February 2026 and run for 18 months.
Health and wellbeing
AI-generated vaccine misinformation
Dr Sam Martin at Manchester Metropolitan University will investigate how AI-generated visual content spreads vaccine misinformation across social media. Sam will be collaborating with SDR UK’s Smart Data Donation Service (SDDS) and Geographic Data Service (GeoDS). By developing Synthetic Discourse Analysis, a new method combining AI detection and social listening with human-in-the-loop qualitative analysis, the Fellowship will generate evidence, tools, and training to support AI digital literacy, community resilience, and UK policy responses.
Proactive healthcare using wearable data
Dr Xiao Gu at the University of Oxford will develop AI models that learn individual health signatures from wearable sensor data to detect early signs of clinical decline. Using foundation models trained on large datasets, the research will develop an AI-driven “Digital Triage Nurse” to enable earlier intervention and support personalised healthcare.
Online environments and mental health
Dr Lewis Paton at the University of York will analyse donated YouTube viewing histories alongside mental health data to examine how online content consumption relates to wellbeing. Using data from the Smart Data Donation Service (SDDS), the project will strengthen evidence for digital mental health policy and responsible platform governance.
Ageing in place and health inequalities
Dr Richard Green at the University of Surrey will link neighbourhood-level smart data with long-running cohort study data to model how health outcomes evolve as people age at home. The research will improve forecasts of local health and care needs and support better place-based planning. Richard will be using data from our Healthy and Sustainable Places Data Service (HASP).
Housing
Cold homes and health risks
Dr Mingyu Zhu at the University of Glasgow will combine smart meter data, housing characteristics, and weather records to model unhealthy indoor conditions. By developing a thermal model and national cold-homes index, the project will help target interventions to reduce: illness, fuel poverty, and health inequality.
Housing quality and vulnerability
Dr Stephen Law at University College London, working with Imago Data Service for Imagery, will combine satellite and street-level imagery with economic data to identify poor-quality homes in vulnerable conditions, leveraging geospatial machine learning methods. The project will produce a new index and planning tool, piloted in London, to target retrofits and better housing policy.
Energy and climate
Electric vehicle charging
Unequal access to electric vehicle (EV) charging risks turning the UK’s net-zero transition into a new source of inequality, particularly for people without off-street parking, those in rural areas, and lower-income communities. Dr Rui Zhu at the University of Bristol will use smart data to map charging accessibility and forecast future demand, providing GeoAI-enabled tools to support a fairer EV transition. Rui will be collaborating with Healthy and Sustainable Places Data Service (HASP) and Smart Energy Data Service (SENSE).
Sustainable biomass expansion
Dr Ce Zhang at the University of Bristol will develop a national geospatial AI system combining satellite imagery, field data, and environmental datasets to guide sustainable biomass production, working with data from our Imago data service. The research will support net-zero planning by balancing carbon, biodiversity, and economic priorities. Ce will be exploring data from Imago Data Service for Imagery.
Forest resilience and ecosystem change
Dr David Milodowski at the University of Edinburgh will fuse satellite, lidar, and meteorological data to model how forests change over time. The project will generate carbon budgets and forecasts to support climate-resilient forest management and policy decisions.
Economic vulnerability
Financial vulnerability and economic hardship
Professor Gbenga Ibikunle at the University of Edinburgh will use anonymised transactions data from the Financial Data Service (FINDS) to model how housing and energy cost shocks affect financial resilience. The project will characterise how financial vulnerability evolves to inform better policy interventions and the development of products that can address financial vulnerability by financial services companies.
Speculative trading and gambling harms
Dr Leonardo Cohen at the University of Nottingham will analyse data from the Smart Data Donation Service (SDDS) to examine how speculative trading overlaps with gambling behaviour and how social media content fuels risky behaviour. The research will support stronger consumer protection and regulation.
Supply chain adaptation to global shocks
Dr Yujie Shi at Aston University will use high-frequency firm-to-firm shipment data to track how UK exporters adapt their supply chains in response to global disruptions, such as trade shocks and logistical crises. By revealing real-time patterns of supplier switching, rerouting, and market exit, the project will help policymakers identify emerging vulnerabilities and design targeted support for businesses operating in volatile trade conditions.
Population and mobility
Inclusive urban mobility
Dr Clara Peiret-García at University College London will combine smart mobility data with traditional surveys to understand how different groups travel in cities. The project will support transport planning that reflects post-pandemic behaviour and avoids disadvantaging specific communities. Clara will be exploring data from Healthy and Sustainable Places Data Service (HASP) and Geographic Data Service (GeoDS).
Population change and local dynamics
Dr Stef De Sabbata at the University of Leicester will integrate smart data on population, health, housing, mobility, and the economy into a population dynamics foundation model capable of generating general-purpose, rich and concise digital fingerprints. The foundation model will help local authorities and businesses analyse change, plan services, and anticipate future demand. Stef will be working with the Geographic Data Service (GeoDS).
Better cultural data
Unlocking cultural and creative data
Bartolomeo Meletti at the University of Glasgow will develop legal and technical infrastructure to manage copyright, data protection, and permissions in digital cultural collections. Working with major institutions such as the British Library, the project will enable safer access to cultural data for research, innovation, and responsible AI.
Joining a community
The 15 Fellows will join SDR UK’s growing community of researchers, including accelerators and Masters students. They will be supported by SDR UK through our national data services, collaborative opportunities, and a platform to influence policy and practice.
Joe Cuddeford, Director of Smart Data Research UK, said:
“Smart data is a valuable UK asset that remains underused for public good. These Fellowships support researchers who can turn that potential into practical impact – from earlier health interventions to fairer energy transitions and action to reduce cost-of-living pressures.
“We are proud to support a cohort that demonstrates how responsible data use can advance knowledge, drive growth, and improve lives.”
SDR UK is the only UK organisation making the full breadth of smart data safely accessible to the UK research community. It has established a family of new data services based at UK universities and research organisations that manage datasets and provide secure access. Many of these Fellowships will work with and through these data services, using smart data that wouldn’t otherwise be available for research to improve lives, communities, and the environment.
