Computer science research strategy
Computer Science is well placed to benefit from the importance of digital solutions in all areas of society which is a driver of the government’s industrial strategy and makes study in this area attractive to potential students. We have critical mass in several areas of computing, notably Computing Methodologies (especially AI, intelligent data analysis and simulation), Human Centred Computing and Software Engineering. We also have world-ranked expertise in Digital Economy and Computational Biology, as well as in employing Computer Science for Social Good.
Our research is ranked 3rd by discipline in the UK by performance ranking of scientific papers and 1st for average citations, H-index and highly cited papers). According to the Research Excellence Framework 2021, more than 80% of its submitted papers were judged 'world-leading' and 'internationally excellent', with the Department also witnessing a 38% increase in terms of ‘Research Power’ during 2014-2021.
Our department aims to create an enabling and inclusive environment which supports students and staff to create positive student outcomes and high quality research with academic and societal benefits.
A department that delivers high quality research with strong academic and societal benefit
| Goal |
Action |
| Build strong internal research groups who support and inspire each other and their research students |
- Work with College to ensure research lab/bench space provision supports collaborative activity within defined research groups and themes.
- Ensure research groups are appropriately resourced including support for maintaining and growing their external presence.
- Encourage research group leads to be involved in supporting the development of academics within their group.
- Support emerging research areas with strong potential including through focussed staff hires where feasible.
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| Maximise research output potential |
- Staff support and recruitment to ensure all T&R staff to have at least one min 3* output and department collectively to have at least 2.5 3* outputs per member of T&R staff.
- Mentoring from highly cited colleagues to help more colleagues produce 4* papers.
- Careful selection of choice of papers for REF submission to optimise outcome including seeking external advice.
- Careful development of 100 word statements for selected REF papers.
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| Maximise research impact potential |
- Department to develop four high quality research impact case studies.
- Department to support activities that support future impact (e.g. consultancy, outreach)
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| Increase proportion of research which is externally funded and numbers of staff securing funding. |
- Mentoring to help in proposal preparation suitable for peer review.
- Departmental events to help develop relevant skills.
- Strong liaison with RSDO for research grant preparation support.
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| Encourage synergies between research themes within the department |
Regular cross-departmental events that encourage communication across disciplinary boundaries. |
| Encourage cross disciplinary and cross department research collaboration |
- Feed into research review to encourage relevant initiatives.
- Cross departmental invites to seminar series.
- Engage with cross university initiatives (e.g. digital health) and cross college initiatives (e.g. digital science hub).
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| Develop external partnerships which strengthen ability to deliver on research goals. |
- Support visits of external visitors leading to joint publications and/or proposals.
- Support staff who wish to develop external links and collaborations with clear potential in terms of future department research outputs, impact and/or funding.
- Support college and university initiatives for collaboration with overseas institutions where there is potential in terms of future department research outputs, impact and/or funding.
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| Achieve good PhD completion rates |
- Admission of only suitably qualified applicants.
- Support high quality PhD training.
- Ensure adequate desk space and resources to support PhD programme.
- Robust annual review process for PhD progression.
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