Introduction to our research
The School of Computer Science was established 30 years ago and is firmly established as a leading centre for computer science research.
Our world-leading research tackles difficult real-world problems that often have high impact on industry, commerce and the public.
It involves a shared ethos of 'computing in the world', in which fundamental advances in computer science are connected to knowledge and methods from other disciplines to enable deep collaborations with research users in diverse sectors.
Join our future research leaders
World-class talent, working in multidisciplinary teams and with inspiring leaders, are at the heart of capturing new ideas and translating these into world-changing solutions.
As a research-led institution, the University of Nottingham recognises the value and contribution of early career researchers in delivering its ambitious, high-quality research vision. In order to enhance this vital aspect of our research network we will recruit 100 Nottingham Research and Anne McLaren Fellows by the end of 2020.
Click here to find out more and how to apply
We organise our research through seven research groups who cover many sub-disciplines of computer science. Our research covers a diverse range of interdisciplinary areas, informs our teaching and has strong links with industry.
Research in the Agents Laboratory spans the specification, design and implementation of agent-based systems, including logics for agents, agent programming and verification, and the application of agents in simulation and virtual environments.
Automated Scheduling, Optimisation and Planning Group (ASAP)
The ASAP research group carries out multi-disciplinary research into mathematical models and algorithms for a variety of real-world optimisation problems under uncertainty.
Computer Vision Laboratory (CVL)
The CVL performs basic and applied research in image manipulation, analysis and computer vision. Our goals are to develop novel and efficient techniques for the extraction of quantitative descriptions of viewed objects from a variety of images and image sequences, and to translate those techniques into high quality software tools that can be used to address real world problems.
Data Driven Algorithms, Systems and Design (DAS)
DAS Research fosters a cross-disciplinary approach to data science by developing machine learning and data mining algorithms and adopting principles of user centred design to maximize the synergy between human intelligence and cyber-physical systems.
Functional Programming Lab (FPL)
The aim of the FPL is to develop simple but powerful techniques for writing and reasoning about programs, by recognising and exploiting their underlying mathematical structure.
Intelligent Modelling and Analysis (IMA)
The IMA group has established itself as a unique brand in the UK for end-to-end data modelling and analysis. We are a highly inter-disciplinary research group focusing on the development of models and techniques for real-world and multifaceted problems in data analysis.
Lab for Uncertainty in Data and Decision Making (LUCID)
The Lab for Uncertainty in Data and Decision Making (LUCID) was founded in early 2016. It brings together a number of researchers with the purpose to advance our understanding of how to capture, model and reason with uncertain data.
Mixed Reality Laboratory (MRL)
The MRL is a dedicated studio facility within The University of Nottingham where computer scientists, psychologists, sociologists, engineers, architects and artists collaborate to explore the potential of ubiquitous, mobile and mixed reality technologies to shape everyday life.
The impact of the School’s research is enhanced through interdisciplinary research.
Further information about the School’s postgraduate research programme is available here.
Research in Malaysia
The School's research activity at the Malaysia Campus is focused on the investigation and development of Intelligent Computing Systems.
Research Administration and Support Team
The Research Administration and Support Team for the School of Computer Science can be contacted at email@example.com for general queries about our research.