Research teams

Team Leader: Professor Liam McDaid

A major focus of the CNET research group is the development of computational models of brain function and to exploit the properties of neural based systems in the development of new computing paradigms in software.

Specifically our computational models serve to deepen our understanding of the specific signalling pathways that brain cells use to communicate with each other. These pathways are orchestrated by a complex biochemical and biophysical processes occurring at the cellular and network level.

Our approach is to implement multi-scale models of neural and neural-glial networks with specific interest in understanding the synaptic and cellular mechanisms underpinning plasticity.

CNET is also focused on taking inspiration from these brain models in the development of new intelligent computational systems.

The CNET group is currently developing a novel astro-centric hardware platform (EMBRACE) to support acceleration and emulation of key neural behaviours.

The platform will open up a new direction of research whereby neuroscientists and computational neuroscientists will be able to explore the complex and detailed interactions between glial and neurons at the level of networks and also how these interaction play out in both the functional and dysfunctional brain.

Team Leader: Professor Sonya Coleman

The cognitive robotics team focuses on novel, advanced control methods for autonomous robots, merging approaches from artificial intelligence, cognitive science and engineering.

Reflecting the increasing importance of autonomous robotics in industries such as the service industry and healthcare, research in cognitive robotics at the ISRC ranges from investigating the foundations of robotics (robotics as a science) to applications of robotics, particularly in the area of assistive robotics.

The team publishes in the areas of cognitive mobile robotics, robot manipulators, machine learning, tactile sensing, biologically-inspired approaches to robot control, robot ecologies, artificial intelligence, computer and robot vision, object recognition and manipulation and pattern recognition.

The cognitive robotics team has been involved in successful EU projects such as ImCLEVER and RUBICON and in currently co-ordinating the FP7 VISUALISE project and involved in the FP7 SLANDAIL project. The team has secured research funding from sources including The Leverhulme Trust, The Nuffield Foundation, The Daiwa Foundation, EPSRC and the EU Framework programme.

Team Leader: Professor Girijesh Prasad

The team’s research focus is on understanding neuronal dynamics, particularly how brain regions interact and co-ordinate in order to accomplish day-to-day cognitive tasks as well as autonomic functions in resting state. In particular, there is a greater emphasis on investigating variations in functional and effective connectivities among various brain regions during cognitive processes and pathological conditions through forward and/or backward modelling approaches.

This is with the central objective of advancing diagnosis as well as of devising stratified treatment and rehabilitation strategies for various nervous system disorders such as stroke, Alzheimer’s disease, ALS, spinal chord injuries, depression, and epileptic seizures. The brain signals acquired through non-invasive neuro-imaging modalities of EEG and MEG are primarily made use of in our investigations.

The team’s R&D is very actively contributing towards advancing neuro-technology primarily in two ways: developing computationally intelligent bio-signal processing & analysis algorithms and devising practical brain-computer interfaces (BCIs).

The BCI systems are developed mainly based on the processing of brain signals with the primary objective of increasing independence and improving the quality of life of people with disabilities due to old age, injury or disease.

These systems facilitate real-time translation of the electrical activity of the brain (acquired from electrophysiological signals such as EEG or MEG) into commands to control devices. They do not rely on muscular activity and can therefore provide communication and control for those who are severely paralyzed (e.g., locked-in).

These systems may also help actuate a supportive rehabilitation device resulting in enhanced motor restoration in those suffering from upper limb and/or lower limb paralysis.

Beyond medical applications, a practical BCI offers general users an additional and independent communication channel based on trained brain signal patterns alone. This opens up promising opportunities for a range of novel applications such as computer games with intuitive control strategies and advanced virtual reality (VR) scenarios.

Team Leader: Professor Kevin Curran

Ambient Intelligence (AmI) refers to electronic environments that are sensitive and responsive to the presence of people.

In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in easy, natural ways using information and intelligence that is hidden in the network connecting these devices.

Games research interests are focused on Experiential Based Learning in Virtual environments, VLE\Virtual World Integration, Hardware\Virtual World Integration and Virtual\Augmented Reality and perceptual computing.

This research team at the ISRC has a combined experience of many decades with multi-disciplinary backgrounds in areas including concurrent and distributed systems; virtual worlds, serious games, computer networking; health technologies; pervasive computing; internet security, mobile and perceptual computing.