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Details of Grant 

EPSRC Reference: EP/R018634/1
Title: Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics
Principal Investigator: Murray-Smith, Professor R
Other Investigators:
Daly, Dr R Ntarmos, Dr N Ounis, Professor I
Macdonald, Dr C Anagnostopoulos, Dr C Yuan, Dr K
Williamson, Dr J Jensen, Dr B S Husmeier, Professor D
Gollee, Dr H TRIANTAFILLOU, Professor P Rogers, Dr SD
Hong, Dr J
Researcher Co-Investigators:
Project Partners:
Amazon Web Services (Not UK) J.P. Morgan (UK) Skyscanner
The Data Lab Widex A/S (International)
Department: School of Computing Science
Organisation: University of Glasgow
Scheme: Standard Research
Starts: 01 May 2018 Ends: 30 April 2022 Value (£): 3,055,465
EPSRC Research Topic Classifications:
Artificial Intelligence Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
09 Oct 2017 New Approaches to Data Science Interviews 9 and 10 October 2017 Announced
Summary on Grant Application Form
Progress in sensing, computational power, storage and analytic tools has given us access to enormous amounts of complex data, which can inform us of better ways to manage our cities, run our companies or develop new medicines. However, the 'elephant in the room' is that when we act on that data we change the world, potentially invalidating the older data. Similarly, when monitoring living cities or companies, we are not able to run clean experiments on them - we get data which is affected by the way they are run today, which limits our ability to model these complex systems. We need ways to run ongoing experiments on such complex systems.



We also need to support human interactions with large and complex data sets. In this project we will look at the overlap between the challenge someone faces when coping with all the choices associated with booking a flight for a weekend away, and an expert running complex experiments in a laboratory.

The project will test the core ideas in a number of areas, including personalisation of hearing aids, analysis of cancer data, and adapting the computing resources for a major bank.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
Date Materialised
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Further Information:  
Organisation Website: http://www.gla.ac.uk