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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.



Overview

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 - Position Vacant
  • Manchester - Position Vacant
  • Newcastle - Stephen McGough, Senior Lecturer, School of Computing
  • Sheffield - Ning Ma, Lecturer in Medical Computing, School of Computer Science
  • York - Nick Zachariou, Ernest Rutherford Fellow, School of Physics, Engineering and Technology

We have created a dedicated N8 CIR Slack workspace for you to connect with others in the N8 community and share recent publications and ideas that you would like to find new collaboration partners for, discuss upcoming funding calls and suggest meetings and sandpit events that you'd like us to host. Join us by clicking the link below or find out more on our webpage.

Join the N8 CIR Slack workspace


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