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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.
Data-driven design assurance
Using text mining and natural language processing to provide insight into design assurance practices; the process of assuring the right job is done the right way
Living with machines
Harnessing digitised archives and collaborations between historians, data scientists, and curators, to model the effects of mechanisation on society
Policy priority inference
Developing computational and network methods to advise governments on the policy priorities needed to reach socioeconomic development goals
Vote trading networks
Building network science and data science methods to uncover hidden cooperation in democratic institutions
Retrofit design in the built environment
Exploring decision making processes common in construction and building management, to evaluate potential opportunities for retrofitting in the built environment
Investigating industrial CT scanner damage
Gathering community-sourced data on damage to x‑ray detectors in industrial CT scanners, to inform cost-effective maintenance
AI for precision mental health
Producing AI tools than can personalise mental health profiles and advance the precision of early diagnosis and subsequent treatment
Neural networks with natural language explanations
Developing neural network models that can both learn from natural language explanations and use them to explain their decisions
Discovering polarity change in word meanings
Advancing computational and mathematical models to discover the change in words’ polarity, from positive to negative or vice versa, in large-scale web archives
Data-driven experiment design
Developing new statistical tools to select the most informative biological laboratory experiments to perform, to maximise learning and minimise research costs
Crowdsourced and citizen science
Establishing best practice guidelines for gathering and analysing data from crowdsourced and citizen science experiments
High performance, large-scale regression
Investigating the effectiveness of distributed computer systems for running regression analysis, a process which determines the relationships between large numbers of variables
Developing an ethical framework for explaining algorithmic decision-making
Explaining the processes, services, and decisions delivered by AI, in conjunction with the Information Commissioner’s Office
Political volatility
Using techniques such as natural language processing to quantify trends and changes in the volatility of public opinion before and after widespread use of social media
