Machine Learning

Machine Learning sits at the heart of a large number of modern data processing models and the N8 CIR is building a community of researchers to share experiences and methodologies.


The importance and relevance of Machine Learning and AI are only likely to increase. Despite the rising popularity of this methodology in CIR many Machine Learning practitioners operate independently, overcoming challenges and barriers in isolation when collaboration may help them to resolve issues quickly and with greater success.

One of the key drivers for the N8 CIR theme will be bringing together Machine Learning researchers and helping them to collaborate and share ideas and best practices.

We will work to identify common barriers and challenges faced by those looking to integrate Machine Learning into their research and develop activities such as training and sandpits where they can compare their methodologies to ensure they can overcome the problems they are facing.

Academic Theme Leads

The theme leads for each institution are:

  • Durham - Noura al Moubayed, Assistant Professor, Department of Computer Science
  • Lancaster - Christopher Nemeth, Professor in Statistics
  • Leeds - Serge Sharoff, Professor of Language Technology
  • Liverpool - Maya Wardeh, NPIF Research Fellow, Institute of Infection, Veterinary and Ecological Sciences
  • Manchester - Alex Skillen, Lecturer in Engineering Simulation and Data Science, Department of Mechanical, Aerospace & Civil Engineering
  • Newcastle - Stephen McGough, Senior Lecturer, School of Computing
  • Sheffield - Position Vacant
  • York - Nick Zachariou, Ernest Rutherford Fellow, School of Physics, Engineering and Technology

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