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The department’s research aim is to continue developing its research culture, capacity and international reputation. We are committed to engaging in knowledge generation, applicable research and enhanced societal impact activities. Expertise is housed in the research centre and visual computing lab and it is primarily focused around smart data analytics and visualisation, disruptive technologies and smart applications, cyber security, autonomous systems and robotics, telecommunications, computer vision, augmented and virtual reality.

If you would like to find out more about our research, please get in touch.

Centre for Data and Complex Systems Research

Director: Professor Nik Bessis

Deputy Director: Professor Yannis Korkontzelos

The research centre has been formed to support the development of an environment of international excellence in the areas of computer and data science with a particular emphasis on smart data analytics, data representation and visualisation, cyber security, interoperable and interconnected distributed applications and technologies and smart infrastructures, AI and autonomous robotics, telecommunications, IoTs and other disruptive services and technologies. The research centre is structured into five high-level research groupings:

Smart data analytics
Smart systems and applications
Cyber security
Robotics and autonomous systems
Communications systems

Visual Computing Lab

Director: Professor Yonghuai Liu

The lab focuses on the topics in the general areas of 3D computer vision, image processing, pattern recognition, visual data analytics, computer graphics, virtual/augmented reality, human sensing and human-robot social interactions. The research is supported by the latest technologies such as  the Computer Augmented Virtual Environment (CAVE) and a range of state-of-the-art devices for data acquisition, output, visualisation, and full immersive experiences including: Tobii Eye X, Vive, Z-Space, Kinects, Hype Box, Emotive, Enobio BCI, Nao Robots, 3D Scanner and printer. It has the following goals:

  • connecting with stakeholders to impact society
  • supporting students to test the latest visual computing techniques and acquire research-lead employability skills
  • empowering researchers to solve theoretical and real-world problems in visual computing and utilising virtual and augmented reality technology.

It aims to:

  • Visualise the signal, image, shape and video data and their operations with the modern CAVE and other devices.
  • enhance the visual data for high contrast and removal of unwanted factors,
  • analyse and convert the visual data into semantically meaningful components, models, measurements, relevant knowledge and/or interesting responses and behaviours
  • explore data visualisation and AR/VR simulation and applications in the real world such as medical imaging, training, computer aided instruction, CAD, systems automation, additive manufacturing, plant science, robotics, autonomous vehicles, intelligent surveillance, remote sensing, industrial quality assurance, and others.

It currently focuses on, but is not limited to, the following areas:

3D computer vision
image processing
Pattern recognition
Computer graphics, virtual/augmented reality, visualisation
Human sensing and human-robot social interaction
Lab members

Data Science STEM Research Centre

Our strategic target for growth in Data Analytics has enabled the department of Computer Science to found and lead an interdisciplinary STEMM research centre, which draws expertise from multiple subjects across the University.

Outcomes and activities

Our research work is captured in:

We also have impact case studies:

Developing simulation software in order to improve technology enhanced learning of modern computer architecture

Teaching and learning of computer architecture has been enhanced using highly interactive simulations with carefully constructed visualisations and animations. Computer scientists need to understand and observe how different parts of a modern computer system’s architecture and organization fit together, interact and support each other. Unique educational simulation software has been designed, developed and evaluated with these requirements in mind. Since the software and teaching materials have been made public, numerous universities worldwide adopted it in their courses with claimed positive impact on student engagement, course popularity, grades, speed of delivery of curriculum, attendance and peer recognition of best practice.

Improving quality assurance of a large software model through relative debugging

As a result of collaborative commissioned research, the lead developers of a major atmospheric research and operational weather forecasting model have changed their approach to quality assuring model source code. Drawing directly on the research findings, the lead developer has taken the decision to adopt a new approach to the correction of inconsistencies and inefficiencies in source code and to alter the software build procedure to be followed by a large model development community. An additional impact, in the form of improved business competitiveness, is felt by a British software and consultancy company, which has been able to enhance a key tool used in their quality assurance and platform migration work with a global client base.


Academics, post-doctoral and PhD researchers have access to cutting-edge facilities including state-of-the-art software (SAS, Matlab, Unity, and others) and hardware (high-end servers, robots, transparent touchscreens, Hololens, VIVEs and the first 4K CAVE installed in a UK academic institution).

The department has also an established community of Postgraduate Researchers undertaking research in different areas of computer science. We operate under a university research governance and ethics framework.