Computer Science

Developing tomorrow's technology to solve today's problems. 

Head of Subject

Dr Peter Chapman
Head of Computer Science

Computer Science


The Computer Science group at Edinburgh Napier delivers world-class research and enterprise in the areas of artificial intelligence, data science and visualisation, games development and software engineering. The latest UK national research assessment (REF 2021) places us as third best in terms of research power in Scotland. With respect to research impact, we are a leading UK university with 100% of our assessed work from areas of computing achieving the highest rating (4* = ratef as world-leading), a recognition achieved only by six other universities in the UK. Based on the Times Higher Education Ranking 2023, computer science at Edinburgh Napier is ranked third among computer science departments in Scotland, and in the top 400 in the world.

Computer science is developing at an ever-increasing pace, and is affecting the world in endless new ways. Things that were a pipe dream only a decade ago, such as digital assistants that we can talk to, or autonomously driven cars, are today a reality. At Edinburgh Napier, we are committed to driving new theory and its development into technology, while ensuring that this can be readily applied to solving the most pressing real-world problems. We have been awarded funding for core research from national and international research councils including the Engineering & Physical Sciences Research Council, European Commission, and Innovate UK. We regularly work with industrial partners to harness the latest research to solve their problems, and receive government funding for this through Innovation Vouchers and Knowledge Transfer Partnerships.

Our Key Research Themes

Artificial Intelligence

Our artificial intelligence research focuses on intelligent agents, machine learning, natural language generation, and nature-inspired optimisation. We develop fundamental theory in areas including argumentation and dialogue theory, computer vision, deep learning, evolutionary computation, multi-agent systems, and reinforcement learning.  We apply this to a wide range of application areas including conversational AI, industrial scheduling and timetabling problems, medicine and health, malware detection, policy making, robotics, smart energy, social simulation, and understanding trust between people and AI. 

Data Science 

Our data science and visualisation research focuses on data analytics, effective visual representations, explainability, real-time visualisation in virtual reality, and topic modelling. Our key application areas include analysis of biological data, big sensor data, health and social care, real-time computer vision for facial and body tracking, and real-time 3d simulations using GPU programming. 

Games Engineering

Our games engineering research is aligned with the state of the art in industry.  Various aspects of games development is being investigated by our researchers with special focus on rendering techniques and technologies.  One of our spin-offs was recently acquired by Disney in U.S. Currently the games development research staff are involved in various large scale projects like CAROUSEL project that is funded by E.U.

Software Engineering

Our software engineering research focuses on empirical software engineering, mining software repositories, compiler design, cloud and edge computing, cyber physical systems, green computing, internet-of-things, micro-service oriented architectures, and secure software development. We are especially interested in the application of artificial intelligence to the above areas.


We are especially interested in excellent impact-oriented research. For example, in the Games area, we collaborate with large corporations such as Disney, Epic Games, Meta and Roblox as well as supporting SMEs, including Edinburgh Napier augmented reality spin-off, 3Finery Ltd and immersive technology company Cobra Simulation Ltd. Recent Knowledge Transfer Projects (KTPs) have drawn on our skills in NLG (with Verint) and in accelerating hardware for machine-learning applications (CodePlay Software Ltd). Our optimisation activities assisted with transportation planning during the COVID-19 lockdown.


Examples of our work in the media include:

Our Research Projects 

Sample research projects held by group members include

Our Degree Programmes 

We also support Graduate Apprenticeships in areas including software development and data-science.


State of the art and high-end computing facilities are utilised by our group to provide an excellent research and teaching experience to our staff and students.  The labs and computing facilities are distributed around the Merchiston campus.  The Jack Kilby Computing Centre provides variety of computing facilities and is open 24-hours a day throughout the week.

We also currently host two specialist research labs. Our Computational Sustainability Lab pursues a transformative research agenda concentrating the attention and efforts of computer scientists on the challenges around sustainability. To achieve this, the lab provides facilities for working with Internet of Things (IoT) systems that gather data via sensors, so that it can be used for modelling and advanced analytics. Lab users have access to a stock of development boards, electronic components and manual and electrical tools as well as dedicated project storage space. A feature of the physical environment is the living display where long-running projects are arranged on a re-configurable peg wall. The Lab is designed to be easily converted into ‘presentation mode’ for events and is equipped with fully-featured videoconferencing facilities for remote participants.

Our Robotics Lab offers a space for mobile and swarm robotic experiments. The lab is composed of an arena with multiple cameras for tracking the robots' movements. We have several models of small two-wheeled robots which are well suited for single robotic navigation tasks or multiple robotic tasks such as emergent behaviours or collaborative tasks. The lab is used for research and education in swarm robotics, evolutionary robotics and reinforcement learning.