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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.
The Turing AI scientist grand challenge
Developing AI systems capable of making Nobel quality scientific discoveries highly autonomously at a level comparable, and possibly superior, to the best human scientists by 2050.
Causal inference for improved cybersecurity threat detection
Understanding the causal links in the tactics and techniques of cyberattacks
Data science for tackling modern slavery
This project aims to develop innovative tools to assist the prevention, pursuit and prosecution of perpetrators and to support victims
Adaptive multilevel MCMC sampling
Developing an MCMC algorithm for efficient Bayesian inference in multilevel models
Shocks and resilience
Measuring policy impact in the COVID-19 crisis and building resilience against future shocks
Uncertainty quantification for black box models
Developing methods for the quantification of uncertainty in complex numerical models
Digital twin of the world’s first 3D printed stainless steel bridge
A revolutionary project to create the world’s first 3D printed steel pedestrian bridge, innovating across multiple disciplines to transform design and construction and gain greater understanding of how infrastructure can act as a living object
Vulnerability to misinformation during COVID-19
Providing insight into people’s vulnerability to accepting health-related misinformation during COVID-19
Synthetic Data Generation for Finance and Economics
Generating artificial business, finance, and economic data to enable data sharing, scenario simulation, and model validation
Statistical machine learning for randomized clinical trials (MRC CTU)
Developing and applying machine learning methods to improve the design, conduct and analyses of clinical trials
Risk prediction in adult cardiac surgery
Using machine learning to identify patients who are likely to not survive open heart surgery in the UK
