Machine Learning


Machine Learning aims to develop algorithms which automatically learn to recognize complex patterns in data, and use these to make intelligent decisions.

The Machine Learning group forms part of the Department of Computer Science, University of Sheffield. It has gained an international reputation for research into the development of machine learning techniques and their application to a diverse range of modelling tasks.

Major research themes in the ML group include:

  • Artificial Intelligence
  • Brain Imaging
  • Computational Systems biology
  • Computational Neuroscience
  • Gaussian Processes
  • Personalised Health
  • Optimisation
  • Tensor Analysis and Learning

The group organises the Sheffield Machine Learning Seminar Series on machine learning related topics.

The group is always interested in good candidates for research student positions. Please contact one of the group members for further details.

The Machine Learning group has collaborative links with the Speech, Natural Language Processing and Complex Systems Modelling groups.

machine learning word cloud

Group members

Core and Affiliated Academic Staff:

Research Software Engineer:



June 2017

Prof Vasilaki attended the Leverhulme Centre for the Future of Intelligence (CFI) and Royal Society Machine Learning dialogues workshop on Sheffield as expert. The workshop’s aim is to conduct public dialogues on attitudes to machine learning and its potential benefits and risks, focusing on the views of ‘digital natives’.

Professor Eleni Vasilaki comments in the New Scientist article: AI will be able to beat us at everything by 2060, say experts.

January 2017

Prof. Eleni Vasilaki gives the keynote talk for the Research software management, sharing and sustainability workshop, Sheffield. 

Welcome the arrival of Dr Mauricio Alvarez.

November 2016

Prof. Eleni Vasilaki is quoted in the New Scientist

Welcome the arrival of Dr Haiping Lu.

October 2016

Eleni Vasilaki is promoted to Professor. 

August 2016

Dr Eleni Vasilaki is named the new Head of Machine Learning group.

Prof. Neil Lawrence is taking up a position with Amazon.

Dr Eleni Vasilaki joined the Editorial Board of Scientific Reports, Nature Publishing Group.

Two new lecturers join the Machine Learning group.

July 2016

The University of Sheffield named an NVIDIA GPU Education Center

Dr Eleni Vasilaki is an academic visitor at Macquarie University, Australia. 

June 2016

Prof. Neil Lawrence: Data trusts could allay our privacy fears

May 2016

Prof. Neil Lawrence: Google's NHS deal does not bode well for the future of data-sharing

January 2016

Prof. Neil Lawrence: Google AI versus the Go grandmaster – who is the real winner?

December 2015

Prof. Neil Lawrence: OpenAI won't benefit humanity without data sharing

November 2015

Prof. Neil Lawrence: The information barons threaten our autonomy and our privacy

Dr Eleni Vasilaki delivers a mini seminar series in Computational
Neuroscience titled "unsupervised learning in neural networks” for the
MSc and PHD students of Biomedical Science, Physics and Computer Science, University of Antwerp

August 2015

Prof. Neil Lawrence: How Africa can benefit from the data revolution

Older news

July 2015

Prof. Neil Lawrence: The data-driven economy will help marketers exploit us

June 2015

Prof. Neil Lawrence: How to prevent creeping artificial intelligence becoming creepy

April 2015

Prof. Neil Lawrence: Let's learn the rules of the digital road before talking about a web Magna Carta

Events and Talks

Open Data Science Initiative

Do you want to hear or talk about data science in Sheffield? Come along to one of our Data Hide meetings (held at “The Hide” in Sheffield).

Open data science is a philosophy designed to address emerging challenges for society in data. The Open Data Science Initiative is a cross faculty project built around the ideas in this white paper.

Staff talks

Prof. Neil Lawrence

Dr Eleni Vasilaki


Open source resources

RODA (Rodent Data Analytics)

This repository hosts code that can be used to analyse the trajectories of animals be means of a semi-supervised clustering algorithm.



Tune your algorithms and your design wetlab experiments.  GPyOpt is a Python open-source library for Bayesian Optimization developed by the Machine Learning group of the University of Sheffield. It is based on GPy, a Python framework for Gaussian process modelling.


GPy (Gaussian processes framework in python)

GPy is a Gaussian Process (GP) framework written in python, from the Sheffield machine learning group.

Gaussian processes underpin range of modern machine learning algorithms. In GPy, we've used python to implement a range of machine learning algorithms based on GPs.



Machine Learning Research Group
Department of Computer Science
University of Sheffield
Regent Court
211 Portobello
Sheffield, S1 4DP

Tel: +44 (0)114 222 1800
Fax: +44 (0)114 222 1810

Information about getting to the university, including maps and travel information, is available.