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Turing Research Projects

Our Turing Fellows lead a wide range of projects.

Data science and biomedical research

Researchers at Newcastle University are helping to envision the future of healthcare in the UK with Turing research projects. This project is using ‘big health data’ to:

  • improve people’s quality of life
  • reduce healthcare costs
  • improve the effectiveness of healthcare

It addresses the challenges of new data-driven models that will revolutionise healthcare, such as translating population scale big datasets into models that predict the early onset of disease.

Turing Fellow and Principal Investigator: Dr Paolo Missier paolo.missier@ncl.ac.uk

Visualising big data for the widest range of people

The Turing research project is addressing a growing gap in data science that links data analytics results to human cognition and decision making. Knowledge derived from data needs to make sense to stakeholders for it to have the greatest impact.

The Turing research research will exploit the power of cloud computing to automate 3D/4D visualisation that will investigate visualisation optimisation using fixed models of human vision, then later seeks to develop self-learning models.

Turing Fellow and Principal Investigator: Prof Nick Holliman nick.holliman@ncl.ac.uk

Smart cities and inequality

Research from the Spatial Analytics and Modelling (SAM) group, the Centre for Urban and Regional Development Studies (CURDS), and the Urban Observatory is investigating spatial inequities in sensor deployment and coverage in the Smart City. It focuses on the identification of coverage gaps and investigates how such gaps are associated with locations of vulnerable populations.

Turing Fellow and Principal Investigator: Prof Rachel Franklin rachel.franklin@ncl.ac.uk

Explore our Cities research

Data for monitoring neurological conditions and disorders

The Turing research project is developing novel statistical models for precision monitoring and timely diagnosis of neurological conditions and disorders, enabling real-time evidence-based decision making. It will apply these models to low-cost monitoring and diagnosis tools for upper limb rehabilitation after stroke and age related neurodegenerative diseases such as dementia and Parkinson’s disease.

Turing Fellow and Principal Investigator: Dr Jian Shi jian.shi@ncl.ac.uk

Boosting manufacturing productivity through AI

The research will demonstrate potential advantages of AI for visual inspection in high volume manufacturing across a range of industries.

Using embedded GPU computing that takes images from low-cost cameras, which input into deep learning algorithms, it aims to:

  • improve the efficiency and effectiveness of visual inspection
  • significantly improve UK manufacturing productivity

Turing Fellow and Principal Investigator: Prof Nick Wright nick.wright@ncl.ac.uk

Streaming data modelling for real-time monitoring and forecasting

The project will address one of the key challenges of the big data age: the development of scalable algorithms for extracting useful information from large, complex, heterogeneous, and ever-growing datasets in near real-time.

New methods will be developed, motivated by stress-testing robust new implementations of the best available online inferential algorithms in two demanding application areas.

Turing Fellow and Principal Investigator: Prof Darren Wilkinson darren.wilkinson@ncl.ac.uk

Deep learning

Deep learning uses artificial neural networks to identify key features of input data and combines these features in order to accomplish tasks which have historically been seen as requiring human intelligence.

It has the potential to solve many of today’s big data challenges, however, there is no easy way to identify a priori the best deep learning network for solving a particular problem. This project is developing algorithms and techniques to identify more quickly the best artificial neural network to solve the challenges of companies, government agencies and universities.

Turing Fellow and Principal Investigator: Dr Stephen McGough stephen.mcgough@ncl.ac.uk