Research teams

The Neuromorphic Engineering team develops brain-inspired computing architectures, algorithms and hardware that reproduce key principles of biological neural information processing.

Research focuses on spiking neural networks, neural architectures, neuromorphic hardware, reconfigurable computing, neural and neural-glial models, event-driven processing, sensory computation, adaptive learning and resilient or self-repairing intelligent systems.

The team investigates how biological principles can be translated into efficient computational systems capable of processing sensory information in real time. Research includes implementations of neural systems on reconfigurable hardware, neuromorphic acceleration, brain-inspired vision and sensory processing, and the development of adaptive and fault-tolerant computing architectures.

Applications span robotics, intelligent sensing, medical and industrial signal processing, process control and energy-efficient AI.

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.

NeuroAI and Neurotechnology (NAINT) Research Team

Team Leader: Professor KongFatt Wong-Lin

The NeuroAI and Neurotechnology team investigates the relationship between brain function, intelligent behaviour and artificial intelligence, while developing technologies that enable interaction with neural systems.

Research spans cognitive and computational neuroscience, neural data science, computational neuroimaging, brain-computer interfaces, neurotechnology, neurorehabilitation and neuro-inspired AI. The team combines experimental neuroscience with machine learning, mathematical modelling, signal processing and computational approaches to understand cognition and develop intelligent technologies.

Research includes the neural mechanisms underlying perception, learning, memory, decision-making and cognitive control, as well as the effects of neurological and neuropsychiatric disorders. The team also develops BCI and neurotechnology applications for rehabilitation, assistive technology, cognitive augmentation and human-computer interaction.

The team operates specialist facilities including the Brain-Computer Interface Laboratory and the Northern Ireland Functional Brain Mapping facility, providing advanced capabilities for neural recording, brain imaging and neurotechnology research.

Human Centred Computing (HCC) Research Team

Team Leader: Dr Pratheepan Yogarajah

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.