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.
Funded
Large Language Models for Vulnerability Detection (Funded)
Supervisor – Dr Kehinde Babaagba
Defeating complex families of malware using evolutionary based adversarial learning (Funded)
Supervisor – Dr Kehinde Babaagba
Quantum Computing for Malware Analysis and Detection (Funded)
Supervisor – Dr Kehinde Babaagba
Trusted-Edge and Semantic-based Approach for Dependable IoT and Smart Systems (Funded)
Supervisor – Dr. Oluwaseun Bamgboye
Identifying artificially generated creative writing (Funded)
Supervisor – Dr Peter Barclay
Language Models for a Low-resource language: Scottish Gaelic (Funded)
Supervisor – Dr Peter Barclay
Adaptive Robot Behaviours in dynamic and outdoor settings (Funded)
Supervisor – Dr Leni Le Goff
Supervisor – Dr Leni Le Goff
Supervisor – Prof. Dr Tomas Horvath
Intelligent Electronic Nose Data Analytics with Applications in Brewing and Distilling (Funded)
Supervisor – Prof. Dr Tomas Horvath
Quantum Software Engineering: Pioneering the Next Frontier in Computing (Funded)
Supervisor – Saima Rafi
Smart Grid Efficiency: Integrating AI and Automation (Funded)
Supervisor – Saima Rafi
Towards a Value-Driven DevOps Pipeline: Integrating Human Values into DevOps Practices (Funded)
Supervisor – Saima Rafi
Exploring gender imbalance in the tech sector: the majority group perspective (Funded)
Supervisor – Prof. Sally Smith
A Personality Orientated Spoken Dialogue System for Realistic Humanoid Robots (Funded)
Supervisor – Dr Carl Strathearn
Supervisor – Dr. Amjad Ullah
Architecture for decentralising intelligence in dynamic cloud-fog-edge compute continuum (Funded)
Supervisor – Dr. Amjad Ullah
The Science of Self-Organizing Swarms for Distributed Edge Infrastructure (Funded)
Supervisor – Dr. Amjad Ullah
Query Performance Prediction Combining Traditional and Neural Information Retrieval Models (Funded)
Supervisor – Dr Md Zia Ullah
Shrinking LLMs using Principled Training Approaches (Funded)
Supervisor – Dr Md Zia Ullah
Self funded
Anticipatory navigation for autonomous robots (Self funded)
Supervisor – Dr Brian Davison
Supervisor – Dr Brian Davison
Talking to robots (Self funded)
Supervisor – Dr Brian Davison
Gendered perspectives of data science (Self funded)
Supervisor – Dr Khristin Fabian
Evaluation of Large Language Models (Self funded)
Supervisor – Dr Dimitra Gkatzia
Evolutionary Robotics (Self funded)
Supervisor – Prof. Emma Hart
An AI-driven approach to proactive Internet of Things (IoT) based systems (Self funded)
Supervisor – Prof. Xiaodong Liu
Supervisor – Prof. Xiaodong Liu
Automating Software Development with Semantic-based Generative AI (Self funded)
Supervisor – Prof. Xiaodong Liu
Data Quality and Cleaning in Big Data (Self funded)
Supervisor – Dr Taoxin Peng
Advancing Software Development and Maintenance through Foundation Models (Self funded)
Supervisor – Prof. Ashkan Sami
Secure Code Generation with Foundation Models (Self funded)
Supervisor – Prof. Ashkan Sami
Machine Learning and Hyper-heuristics (Self funded)
Supervisor – Dr Kevin Sim
Understanding the True Nature of Fitness Landscapes in Evolutionary Computation (Self funded)
Supervisor – Dr Sarah L Thomson
AI enhanced city and mobility design (Self funded)
Supervisor – Dr Neil Urquhart
Improving city mobility with AI (Self funded)
Supervisor – Dr Neil Urquhart
Advancing Explainable Artificial Intelligence (Self funded)
Supervisor – Dr Simon Wells
Advancing the state of the art in Argument Mining (Self funded)
Supervisor – Dr Simon Wells
Reliable Guided Conversational AI (Self funded)
Supervisor – Dr Simon Wells