Intelligent Knowledge Systems
Research in Intelligent Knowledge Systems at the School of Computing Science, University of Glasgow develops distributed intelligent systems for large-scale, heterogeneous and decentralised computing environments. Combining expertise in Distributed Computing, Knowledge Engineering and Distributed Artificial Intelligence, we investigate how systems learn, reason and collaborate across devices, data sources and organisations.
A central theme is Distributed Intelligence: enabling AI beyond centralised data centres. Our research advances Federated Learning, Distributed AI and Trustworthy AI, supporting models deployed across edge devices, cloud platforms and cyber-physical systems. These approaches aim to preserve privacy, reduce communication and energy costs, and improve reliability. We develop algorithms and scalable infrastructures for collaborative machine learning and decision-making, alongside secure data-sharing mechanisms and methods to strengthen robustness, transparency and trust.
A distinctive strength is the co-design of distributed systems and intelligent algorithms, integrating computing infrastructure with Machine Learning and Knowledge Representation. This supports collaborative intelligence emerging from networks rather than a single central platform.
Our research addresses practical challenges through industry collaborations, including a long-term partnership with BMW Group, supporting developments in connected vehicles, digital infrastructure and intelligent industrial platforms. Together, these strengths position Glasgow as a leading centre for research on distributed and trustworthy intelligent systems.
Project Highlights
TERRA: An Intelligent Platform for Integrating Climate Services.
TERRA develops an AI-driven platform that integrates Earth observation data, Digital Twins, and advanced analytics to support climate and water-related decision making. The project combines data from the Copernicus Programme with distributed AI techniques to create scalable services for coastline monitoring, erosion prediction, flood risk assessment, and water pollution analysis. We are developing a Digital Twin of the coastline of St Andrews, enabling AI-driven modelling of coastal erosion and climate impacts. The project demonstrates how distributed intelligent systems can transform Earth observation data into actionable climate services for policymakers, researchers, and environmental agencies.
ELLIE – Internet of Senses for Cultural Heritage
ELLIE explores how AI, Digital Twins, and immersive technologies can transform cultural heritage experiences and creative production. The project develops a distributed platform combining generative AI, Internet of Senses technologies, and virtual environments to enable interactive, multisensory engagement with cultural artefacts and historical sites. We are building a virtual reality and Internet-of-Senses Digital Twin of the Glenlee Tall Ship (Glasgow), allowing visitors to experience the ship in immersive digital environments. The project investigates how distributed AI and immersive computing can support new forms of storytelling, digital preservation, and innovation in the Cultural and Creative Industries.
COIN‑3D – Collaborative Innovation in 3D VLSI Reliability
COIN-3D advances research on next-generation semiconductor systems based on 2.5D and 3D chiplet architectures. The project brings together European research institutions to strengthen collaboration, research capacity, and innovation in advanced microelectronics. We are developing AI-driven approaches to chip design and reliability analysis, applying machine learning and intelligent optimisation techniques to improve the design and performance of complex 3D integrated circuits. By integrating AI with hardware design processes, COIN-3D contributes to the development of future high-performance computing platforms that will underpin distributed AI and data-intensive systems.