Research
Our research
The Research Excellence Framework (REF) 2014 results ranked York's Computer Science:
- 7th overall in the UK;
- 5th for impact;
- 6th for environment.
This result confirms the long-standing global reach and real-world significance of our research and makes us one of best Departments in the country for nurturing excellent research by staff and research students alike. All aspects of our impact and environment were judged to be of world-leading or international standard.
- About our research
- Research groups
- Impact case studies
- Studying for a PhD in Computer Science
- Funding available for PhD places
Research successes
Revolutionary black hole research using quantum mechanics
Research by Professor Samuel Braunstein suggests that information can escape from a black hole - disproving conventional thinking and well-know scientists such as Stephen Hawking. This could revolutionise physics, suggesting that gravity is not a fundamental force of nature.
Meet our researchers
Ian Gray
"My work is centred around the use of new programming models to help the development of complex real-time and embedded systems."
Research area: Programming models for embedded systems
Dr Ana Cavalcanti talks about our research
Ana is former Chair of the Department's Research Student Committee, which looks after research students in Computer Science. Here she gives an overview of research in the Department, talks about how students can get involved in that research, and what facilities we have available. Watch the video of Ana discussing our research facilities.
Featured research
CAPACITIE project: Cutting Edge Approaches for Pollution Assessment in Cities
Professor Peter Cowling and Dr Iain Bate are two of our academics involved in the CAPACITIE project.
Professor Cowling's project, Use of monitoring data and ICT to support city planning decisions, aims to develop a decision support system for reacting to pollution monitoring data.
Dr Bate's project, Capture and analysis of monitoring data, aims to investigate approaches for collecting, processing and interpreting data from a combination of traditional and ‘new’ (less accurate and less reliable) monitoring technologies to produce data that can be used to inform decisions.
Find out more about the CAPACITIE project.
