AI at Nottingham
 
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Scientific Discovery

 

Our adventurous and ambitious AI projects have a clear multi-disciplinary focus and draw upon and influence a range of disciplines and new interdisciplinary application areas. We categorise these as scientific discovery projects.  

Our grounding in diverse applications involves dialogue with many other disciplines for scientific discovery. In addition to health and autonomous systems, we have a variety of AI-driven scientific discovery projects in energy, transport, food sciences, humanities, demographics, physics, chemistry, and engineering.

Highlights from our AI projects

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Plant Phenotyping

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European Plant Phenotyping Network

Johnathan Hirst, man with glasses with blue line patterned background

Royal Academy of Engineering Chairs in Emerging Technology: Prof Jonathan Hirst

 
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University of Nottingham Honorary Fellowship Award: Dr Alan Chamberlain

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Deep machine learning to capture the performance of plants

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Designing Bio-Instructive Materials

 
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Revisiting Optical Scattering With Machine Learning

Dr Tanvir Hussain

EPSRC Fellowship: Dr Tanvir Hussain

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Data CAMMP

 
Predicting deaths based on shopping habits prescription image

Predicting deaths based on shopping habits

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ML to Discover New Hydrogen Storage Materials

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Somatobics - Creatively Embodying AI: Prof Steve Benford

 
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Reducing reduce CO2 emissions through AI

 

University of Nottingham
University Park
Nottingham, NG7 2RD

telephone: +44 (0) 115 951 5151
fax: +44 (0) 115 951 3666
email: Contact us