| 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: |
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| Project Partners: |
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| Department: |
Statistical Science |
| Organisation: |
University College London |
| Scheme: |
Standard Research |
| Starts: |
01 February 2013 |
Ends: |
31 January 2016 |
Value (£): |
674,580
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Human-Computer Interactions |
| Image & Vision Computing |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Panel History: |
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Summary on Grant Application Form |
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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.
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Key Findings |
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No information has been submitted for this grant.
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Potential use in non-academic contexts |
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No information has been submitted for this grant.
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Impacts |
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No information has been submitted for this grant.
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Sectors submitted by the Researcher |
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No information has been submitted for this grant.
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.ucl.ac.uk |