The Chair in Artificial Intelligence (AI) Systems works to advance the design, theory and application of AI systems that are explainable, trustworthy and capable of addressing complex real-world challenges. As AI becomes embedded in everything from healthcare to industrial operations, the need for AI systems that combine data-driven learning with structured knowledge – that humans can understand, trust and interact with – has never been greater. Based in the Department of Computer Science, where the Chair also heads up the Artificial Intelligence Research Unit (AIRU), the Chair’s work spans foundational algorithmic innovation, novel system architectures and forward-looking visions for how AI can shape the future of healthcare, science and urban life.

A central contribution of the Chair’s work is the advancement of hybrid AI architectures for continual learning, interactive scientific discovery and decision-making. These are systems that combine machine learning with structured knowledge representation to improve interpretability, reasoning and overall human-AI system interaction. This includes a comprehensive reference architecture for AI-driven personal health monitoring, hybrid approaches that integrate knowledge graphs with electronic health record data to build explainable disease risk prediction models, and ontology-based frameworks to support scientific knowledge discovery. The Chair has also contributed methodological advances in deep learning, specifically in the emerging area of spatial-temporal graph neural networks for flow modelling.

Looking ahead, the Chair is shaping novel paradigms for human-centred AI, including frameworks for creative, anticipatory AI in urban environments and an interdisciplinary vision for “Smart Living Home” systems that integrate adaptive AI with microbial bioreactors for energy generation, wastewater processing and generating household products.