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Research projects
Focused scientific study, led by Turing researchers, working with other academics and often industry collaborators, towards defined objectives. Turing research projects aim to be multidisciplinary and multi-institutional, delivering both scientific and real-world impact.
A prototype digital twin of the Growing Underground underground farm operated by Zero Carbon Farms Ltd
Computational social science: Social data bias
Investigating social bias in CSS from both a social and computational science perspective
App-based information governance for trustworthy research environments
Delivering an open source 'information governance system in a box' to support data protection in trustworthy research environments
A framework for quantifying the privacy/utility trade-off in generative model based synthetic data
Building a comprehensive picture of privacy and utility for existing generative models
Digital twins for high-value engineering applications (DTHIVE)
Developing digital twins for engineering applications using modelling, data, and connectivity
Quantitative Urban ANalyTics (QUANT)
A land use transportation model simulating the location of employment, population and transport interactions
Impacts of climate change and heat on health
Developing models to quantify the impacts of climate change and increased temperatures on human health
Ground truth for mental health data science
Linking digital footprint data in the UK birth cohorts to guide the next generation of algorithms for mental health and wellbeing research
Marine and maritime group
Helping the marine and maritime industry develop and use data science, machine learning and artificial intelligence
Open Research Community Building
Establishing cross-community collaborations and promoting open research in data science
AI for multiple long-term conditions: Research Support Facility
Developing data standards, best practice and community around AI for multiple long term conditions research
The eye: a window into brain cardiovascular disease
Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease
Future Indonesian Tsunamis: Towards End-to-end Risk quantification (FITTER)
Using high performance computing, uncertainty quantification, and economics to evaluate the risk posed to livelihoods by future tsunamis in Indonesia
Using machine learning to identify patients likely to survive open heart surgery
Developing a new risk calculator using a large dataset from all patients undergoing surgery in the UK
