{"id":4158,"date":"2024-10-23T09:15:36","date_gmt":"2024-10-23T09:15:36","guid":{"rendered":"https:\/\/blogs.napier.ac.uk\/scebe-research\/?page_id=4158"},"modified":"2025-01-28T14:28:55","modified_gmt":"2025-01-28T14:28:55","slug":"computer-science-2025-phds","status":"publish","type":"page","link":"https:\/\/blogs.napier.ac.uk\/scebe-research\/computer-science-2025-phds\/","title":{"rendered":"Computer Science 2025 PhD Projects"},"content":{"rendered":"

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.\u00a0In 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.\u00a0 Based on Times Higher Education Ranking 2023, our computer science is ranked third among CS departments in Scotland.<\/em><\/p>\n

Our artificial intelligence research<\/strong><\/em>\u00a0focuses 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.\u00a0 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.<\/em><\/p>\n

Our data science and visualisation research<\/strong><\/em>\u00a0focuses 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.\u00a0<\/em><\/p>\n

Our software engineering research<\/strong><\/em>\u00a0focuses 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.<\/em><\/p>\n

Our games development research<\/strong><\/em>\u00a0focuses 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.<\/em><\/p>\n

<\/h3>\n

Large Language Models for Vulnerability Detection (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Kehinde Babaagba<\/p>\n

Defeating complex families of malware using evolutionary based adversarial learning (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Kehinde Babaagba<\/p>\n

Quantum Computing for Malware Analysis and Detection (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Kehinde Babaagba<\/p>\n

Trusted-Edge and Semantic-based Approach for Dependable IoT and Smart Systems (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr. Oluwaseun Bamgboye<\/p>\n

Identifying artificially generated creative writing (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Peter Barclay<\/p>\n

Language Models for a Low-resource language: Scottish Gaelic (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Peter Barclay<\/p>\n

Adaptive Robot Behaviours in dynamic and outdoor settings (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Leni Le Goff<\/p>\n

Evolutionary Robotics: Generating diverse and functional robots by jointly optimising their body-plan and controllers (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Leni Le Goff<\/p>\n

Efficient Sensor Data Processing for Decision Support in AgriFood Applications – Beekeeping and Brewing\/Distilling (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Tomas Horvath<\/p>\n

Intelligent Electronic Nose Data Analytics with Applications in Brewing and Distilling (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Tomas Horvath<\/p>\n

Quantum Software Engineering: Pioneering the Next Frontier in Computing (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Saima Rafi<\/p>\n

Smart Grid Efficiency: Integrating AI and Automation (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Saima Rafi<\/p>\n

Towards a Value-Driven DevOps Pipeline: Integrating Human Values into DevOps Practices (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Saima Rafi<\/p>\n

A Personality Orientated Spoken Dialogue System for Realistic Humanoid Robots (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Carl Strathearn<\/p>\n

AI-driven Cloud-to-Things application-level orchestration framework for next-generation Internet of Things systems (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr. Amjad Ullah<\/p>\n

Architecture for decentralising intelligence in dynamic cloud-fog-edge compute continuum (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr. Amjad Ullah<\/p>\n

The Science of Self-Organizing Swarms for Distributed Edge Infrastructure (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr. Amjad Ullah<\/p>\n

Query Performance Prediction Combining Traditional and Neural Information Retrieval Models (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Md Zia Ullah<\/p>\n

Shrinking LLMs using Principled Training Approaches (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Md Zia Ullah<\/p>\n

Anticipatory navigation for autonomous robots (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Brian Davison<\/p>\n

Colebots (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Brian Davison<\/p>\n

Talking to robots (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Brian Davison<\/p>\n

Gendered perspectives of data science (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Khristin Fabian<\/p>\n

Evaluation of Large Language Models (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Dimitra Gkatzia<\/p>\n

Evolutionary Robotics (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Emma Hart<\/p>\n

An AI-driven approach to proactive Internet of Things (IoT) based systems (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Xiaodong Liu<\/p>\n

A unified approach based on semantic models and continuous deep learning to sensor data uncertainty and inconsistency in smart systems (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Xiaodong Liu<\/p>\n

Automating Software Development with Semantic-based Generative AI (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Xiaodong Liu<\/p>\n

Data Quality and Cleaning in Big Data (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Taoxin Peng<\/p>\n

Advancing Software Development and Maintenance through Foundation Models (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Ashkan Sami<\/p>\n

Secure Code Generation with Foundation Models (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Prof. Ashkan Sami<\/p>\n

Machine Learning and Hyper-heuristics (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Kevin Sim<\/p>\n

Understanding the True Nature of Fitness Landscapes in Evolutionary Computation (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Sarah L Thomson<\/p>\n

AI enhanced city and mobility design (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Neil Urquhart<\/p>\n

Improving city mobility with AI (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Neil Urquhart<\/p>\n

Advancing Explainable Artificial Intelligence (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Simon Wells<\/p>\n

Advancing the state of the art in Argument Mining (Self funded)<\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Simon Wells<\/p>\n

Reliable Guided Conversational AI (Self funded) <\/strong><\/a><\/p>\n

Supervisor \u2013 Dr Simon Wells<\/p>\n","protected":false},"excerpt":{"rendered":"

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