Immersive human-centred intelligence (iHCI)

We develop immersive environments powered by machine learning and artificial intelligence to create adaptive, responsive, and human-centred experiences.

Our research explores how AI can personalise content, interaction, and feedback in augmented and virtual reality, supporting learning, training, and decision-making in complex environments.

This theme focuses on the design and evaluation of AI systems that are transparent, trustworthy, and aligned with human needs.

We investigate explainable and responsible AI approaches within interactive systems, examining how users understand, trust, and collaborate with intelligent technologies.

We study brain–computer interfaces and neuroadaptive systems that use machine learning to interpret cognitive and affective signals such as workload, attention, and stress.

This enables intelligent systems, particularly immersive environments, to adapt in real time to the user’s cognitive state, supporting wellbeing, learning, and performance.

This theme explores AI and ML methods for analysing data from wearable devices and sensors, including physiological, behavioural, and movement data.

The goal is to model human state and behaviour in naturalistic settings, enabling personalised, context-aware, and inclusive intelligent systems.

We develop and study robotic systems that incorporate machine learning, perception, and immersive interfaces to support safe, intuitive, and human-aware interaction.

Research includes shared autonomy, human-robot collaboration, and the use of AR and VR to enhance robot understanding, control, and explainability.

This theme addresses emerging forms of interaction, including animal–computer interaction and novel user groups. We apply AI-driven immersive technologies to understand behaviour, cognition, and interaction beyond traditional human-computer contexts, supporting welfare, accessibility, and ethical design.

Across all themes, the group applies machine learning and artificial intelligence as enabling technologies, with a strong emphasis on evaluation, responsible design, and real-world impact. Research outcomes inform teaching, doctoral training, and collaborative innovation.

Trustworthiness and responsibility underpin all research within iHCI. We investigate how immersive and intelligent systems influence trust, autonomy, behaviour, and decision-making.

Our work addresses explainability in AI-driven XR environments, safe human–robot collaboration, ethical use of brain–computer interfaces and wearable sensing, and fairness in adaptive systems.

By embedding responsible AI principles across all themes, iHCI ensures that innovation in immersive technologies remains aligned with societal values and human needs.

iHCI is supported by a fully equipped Live Lab designed for immersive, interactive, and human-centred intelligence research and teaching.

The facility provides access to a wide range of immersive technologies, including augmented and virtual reality systems, haptic and interaction devices, and sensing platforms that support embodied and experiential learning.

The Live Lab enables controlled experimentation as well as hands-on, project-based teaching, allowing students and researchers to design, develop, and evaluate immersive systems in realistic settings.

The group has access to high-performance GPU-enabled computing infrastructure, supporting machine learning, artificial intelligence, and data-intensive experimentation.

This capability enables the development and training of AI models for immersive environments, human sensing, brain–computer interfaces, and robotics, as well as real-time integration with XR systems.

Facilities are closely integrated with teaching at undergraduate, postgraduate, and doctoral levels. Students engage with the Live Lab through taught modules, practical classes, final-year projects, MSc dissertations, and PhD research.

This research-informed approach ensures students gain hands-on experience with industry-relevant tools and methodologies in immersive technologies, AI, and human-centred system design.

The Live Lab also supports interdisciplinary collaboration, enabling students and researchers to work across computing, engineering, design, and applied domains.

Beyond teaching and research, the facilities support PhD training, collaborative projects, and innovation activities.

The Live Lab provides a platform for piloting ideas, testing prototypes, and engaging with external partners, contributing to knowledge exchange and the translation of research into real-world applications.

Teaching activities also emphasise responsible AI design, encouraging students to critically evaluate transparency, bias, safety, and ethical implications within immersive and intelligent systems.