Within the Intelligent Systems Research Centre there are six teams each specialising in a different area of research.
The ISRC is organised in a team structure. We prefer "teams" as opposed to "groups" because we believe in a dynamic environment. This is because teams may grow, merge, expire etc depending on the current research challenges and environment.
Our six teams are:
Computational Neuroscience and Neural Engineering (CNET) Research Team
Team Leader: Dr Cian O'Donnell
CNET works on NeuroAI: developing brain-inspired AI algorithms and neuromorphic hardware, and, in the reverse direction, using AI and computational modelling to understand how the brain works. We collaborate with experimental neuroscientists, distilling their data into principles of adaptive information processing. By studying how synapses and astrocytes coordinate learning in spiking neural networks, we develop smarter algorithms.
Our neuromorphic computer chips, inspired by the brain’s sparse and redundant connectivity, are designed for better signal flow and sustainability. We apply these methods to real-world problems in robotics, health monitoring and agriculture, and apply our biological findings towards brain disorders like multiple sclerosis and autism.
Cognitive Robotics Team
Team Leader: Dr Dermot Kerr
The Cognitive Robotics Team focuses on novel, advanced techniques for autonomous robots, merging approaches from artificial intelligence, cognitive science and engineering.
Reflecting the increasing importance of autonomous robotics in industries such as manufacturing and service, research in cognitive robotics at the ISRC ranges from investigating the foundations of robotics (robotics as a science) to developing new techniques for computer vision and tactile sensing to applications of robotics, particularly in the area of manufacturing and cobots.
The team publishes in the areas of cognitive mobile robotics, computer vision, robot manipulators, artificial intelligence and machine learning, tactile sensing, biologically-inspired systems and smart manufacturing.
Members of the Cognitive Robotics Team lead national projects including the IUK funded Smart Manufacturing Data Hub (£50M), Hartree Centre Northern Ireland Hub (£1.7M), and partners in the IUK funded Industrial Decarbonisation Plan for Northern Ireland and IUK funded SmartNano (£2.5M). The Cognitive Robotics Team is also leading in Proof of Concept technologies with the Neuro-Eye project and are involved in several innovation activities including multiple KTP and Innovation Boost projects.
Cognitive Neuroscience and Neurotechnology (CNN) Research Team
Team Leader: Professor KongFatt Wong-Lin
CNN focuses on understanding the neural basis underlying cognition and behaviour, and their applications to neurotechnology and artificial intelligence (AI). Cognitive functions such as decision-making and dysfunctions such as those related to neurological disorders or affective modulations are investigated. To enable this, the team conducts innovative experiments and undertakes non-invasive neural recordings. Analysis of data involves advanced signal processing, statistical analysis, machine learning, and computational modelling. Biologically based cognitive computational modelling provides further mechanistic insights.
CNN’s practical applications include developing brain-computer interface (BCI) for neurorehabilitation and assistive technologies, collective cognitive systems and gaming, while neuro-inspired AI applications include developing novel intelligent systems. CNN also runs the Northern Ireland Functional Brain Mapping (NIFBM) facility which uses state-of-the-art cryogenic magnetoencephalography (MEG) to measure brain activity.
Human Centred Computing (HCC) Research Team
Team Leader: Professor Joan Condell
The Human-Centred Computing (HCC) team performs research and development in technologies to enhance human wellbeing and address societal challenges, with a focus on health technologies and responsible AI. The research includes creating wearable sensors for remote health monitoring, AI systems that prioritise fairness and ethics, and intelligent rehabilitation tools for independent health management. They also emphasise digital cybersecurity to protect data and maintain trust in AI systems. By integrating AI, sensors, virtual/augmented reality, and machine learning, the team aims to tackle issues like health inequality and accessibility, improving lives and promoting a fairer, more inclusive society through impactful, actionable solutions.
Intelligent Data Analytics (IDA) Research Team
Team Leader: Dr Bryan Gardiner
The Intelligent Data Analytics (IDA) research team draws on new advances in AI to develop intelligent algorithms that can process and analyse complex data from diverse sources, such as visual, textual, and physiological data. By exploring new AI concepts and techniques within areas such as Deep Learning, Computer Vision, and Natural Language Processing, the team aims to extract meaningful insights from large datasets, deciphering complex data patterns and relationships that would be challenging or impossible for humans to identify manually. Their research spans several domains, applying these AI-driven methods to real-world problems such as Healthcare, Finance, and Manufacturing, where understanding such data trends is essential for informed decision-making.
The team’s exploration of Brain-Computer Interfaces (BCI) further enhances their capabilities, focusing on technologies that enable direct communication between the brain and external devices. By analysing neural signals, they develop algorithms capable of interpreting brain activity in real-time, with potential applications in human-computer interaction, assistive technologies, and neurorehabilitation.
In addition, the team conducts research in Extended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). By integrating AI with XR, the IDA team develops immersive, intelligent systems capable of responding to user actions in real-time, thus enabling more dynamic and adaptive environments. This area of research is particularly impactful in fields such as education, skills, and healthcare, where interactive and responsive systems can significantly enhance user experiences.
By combining the strengths of new AI algorithmic development, with advancements in BCI and XR, the IDA research team is pushing the boundaries of intelligent systems.
Computational Materials Engineering (CME) Research Team
Team Leader: Dr Shaun McFadden
CME focuses on the broad discipline of materials science and engineering. A significant focus of CME is on the development and application of Computer Aided Engineering solutions to materials-related processes. Verification and Validation of computational methods is key; therefore, the ability to generate experimental data is critical. Hence, CME team is also skilled at generating experimental data suitable for validation purposes.
CME follows a Materials 4.0 agenda in the development and application of intelligent approaches to solve materials science and engineering problems. Such areas of interest include image processing and classification, application of ML and digital twinning of material processes. Specific areas of interest include the fundamental solidification of metallic alloys, metallurgy, additive manufacturing including metal additive (Powder Bed fusion and Wire Arc Additive Manufacturing), polymer and composites processing.
