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Details of Grant 

EPSRC Reference: EP/K015664/1
Title: ENGAGE : Interactive Machine Learning Accelerating Progress in Science, An Emerging Theme of ICT Research
Principal Investigator: Girolami, Professor M
Other Investigators:
Jones, Professor KE Brostow, Dr GJ
Researcher Co-Investigators:
Project Partners:
Jacobs University Bremen Microsoft Zoological Soc London Inst of Zoology
Department: Statistical Science
Organisation: UCL
Scheme: Standard Research
Starts: 01 February 2013 Ends: 06 January 2014 Value (£): 674,580
EPSRC Research Topic Classifications:
Artificial Intelligence Human-Computer Interactions
Image & Vision Computing
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
06 Nov 2012 Working Together Across ICT Announced
Summary on Grant Application Form
Our vision is to establish and lead a new theme in ICT research based on Interactive Machine Learning (IML). Our expansion of IML will give scientists and non-ICT specialists unprecedented access to cutting-edge Machine Learning algorithms by providing a human-computer interface by which they can directly interact with large scale data and computing resources in an intuitive visual environment. In addition, the outcome of this particular project will have a direct transformative impact on the sciences by making it possible for non-programming individuals (scientists), to create systems that semi-automatically detect objects and events in vast quantities of A) audio and B) visual data. By working together across two parallel, highly interconnected streams of ICT research, we will develop the foundations of statistical methodology, algorithms and systems for IML. As an exemplar, this project partners with world leading scientists grappling with the challenge of analysing enormous quantities of heterogeneous data being generated in Biodiversity Science.
Key Findings
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Potential use in non-academic contexts
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Sectors submitted by the Researcher
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