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 in Computer Science and Informatics category places us as third best for research power in Scotland. In terms of research impact, we are a top U.K. university with 100% of assessed work from areas of computing achieved the highest rating (4* = rated as world-leading). A recognition achieved only by six other universities in the UK. Based on Times Higher Education Ranking 2023, our computer science is ranked third among CS departments in Scotland.
Our artificial intelligence research focuses on intelligent agents, machine learning, natural language generation and evolutionary robotics. 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, malware detection, policy making, robotics, energy, medicine, health, social simulation, and understanding trust between people and AI.
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.
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.
Our games development research focuses on computer graphics, computer vision, video games, visualisation, and immersive technology. We are especially interested in impact oriented research and have had spin offs acquired by large corporations.
Defeating complex families of malware using evolutionary based adversarial learning
Supervisor: Dr Kehinde Oluwatoyin Babaagba
Adversarial Learning for Industrial Control Systems
Supervisor: Dr Kehinde Oluwatoyin Babaagba
Interactive Euler Diagrams
Supervisor: Dr Peter Chapman
Genetic Programming for Diagram Generation
Supervisor: Dr Peter Chapman
Applied Machine Learning And Cybersecurity
Supervisor: Dr Christos Chrysoulas
Sustainability and resilience through federated cloud services in the Internet of Things
Supervisor: Dr Brian Davison
Multi-objective optimisation of sensor network data collection with a mobile gateway
Supervisor: Dr Brian Davison
Generative navigation for autonomous robots using active inference
Supervisor: Dr Brian Davison
Blockchain-based Ecosystem to Combat Fake News
Supervisor: Dr Zakwan Jaroucheh
How Blockchain and NFT Technologies can Fight Counterfeiting and Forgery of Physical Goods and Digital Assets in the Metaverse
Supervisor: Dr Zakwan Jaroucheh
Blockchain Technology and Decentralised Finance (DeFi) : The Bridge to the Future of Finance
Supervisor: Dr Zakwan Jaroucheh
Capture and Contextualisation of Cultural Heritage Data
Supervisor: Dr Babis Koniaris
Using multi-agent systems to help households reduce peak electricity consumption in ways they perceive as fair
Supervisor: Dr Simon Powers
The evolution of institutions for large-scale cooperation
Supervisor: Dr Simon Powers
A Defeasible Ensemble Model of Argumentation Mining
Supervisor: Dr Simon Wells
Stereotypical Patterns of Human & Machine Reasoning for Explainable AI
Supervisor: Dr Simon Wells
Using Formal Dialogue Modules to Guide & Evaluate Conversational AI
Supervisor: Dr Simon Wells
Machine Learning and Hyper-heuristic
Supervisor: Dr Kevin Sim
Semantic Model-Driven Explainable Machine Learning Approach for IoT Applications
Supervisor: Dr Oluwaseun Bamgboye
Enhanced Deep Learning and Semantic-based Predictive Analytics for Reactive IoT Streaming Data and Applications
Supervisor: Dr Oluwaseun Bamgboye
Characterising Automatically Generated Text
Supervisor: Dr Peter J Barclay
Atmospheric Models for Real-time Immersive Rendering
Supervisor: Prof Kenny Mitchell
Real-time Rendering Shape and Appearance with Compact Representations
Supervisor: Prof Kenny Mitchell
Data Quality and Cleaning in Big Data
Supervisor: Dr Taoxin Peng
Exploring gender imbalance in the tech sector: the male perspective
Supervisor: Prof Sally Smith
Artificial Intelligence for Software Engineering (AI4SE)
Supervisor: Prof Ashkan Sami
Software Engineering for Artificial Intelligence (SE4AI)
Supervisor: Prof Ashkan Sami
Supporting Communities through Optimisation of Deliveries
Supervisor: Dr Neil Urquhart
Real-time fNIRS imaging
Supervisor: Dr Shufan Yang
AI enhanced perinatal stroke diagnosis
Supervisor: Dr Shufan Yang
Query Performance Prediction for Sparse and Dense Retrieval Models
Supervisor: Dr Md Zia Ullah