Girijesh Prasad
University of Ulster, Queen's University Belfast, Indian Institute of Technology Roorkee, National Institute of Technology Calicut
Research areas: Neuroscience · Cognitive Neuroscience · EEG and Brain-Computer Interfaces · Gaze Tracking and Assistive Technology · Muscle activation and electromyography studies
0000-0003-3284-9589
About
Prof. Girijesh Prasad is Professor of Intelligent Systems in the School of Computing, Engineering and Intelligent Systems, Ulster University (UU), UK. He is Director of Northern Ireland Functional Brain Mapping (NIFBM) facility at UU’s Intelligent Systems Research Centre (ISRC), where he is a member of NeuroAI and Neurotechnology research team.
He received a BTech in Electrical Engineering from Regional Engineering College (now National Institute of Technology) Calicut, India in 1987, an MTech in Computer Science and Technology from University of Roorkee (now Indian Institute of Technology Roorkee), India in 1992, and a PhD in Electrical Engineering from Queen's University of Belfast, UK in 1997. He is a Chartered Engineer, a Fellow of IET, a Fellow of Higher Education Academy, a Senior Member of IEEE, and a founder member of IEEE Systems, Man, and Cybernetics society’s Technical Committee on Brain-Machine Interface Systems. In 2017, he was awarded the Fellowship of International Academy of Physical Sciences (IAPS) India, and the Senior Distinguished Research Fellowship of Ulster University. Prof. Prasad joined Ulster University, as a Lecturer in 1999; he was promoted to Senior Lecturer in 2007, Reader in 2008, and Professor in 2011. Previously he worked in industry first as a Digital Systems Engineer and then as a Power Plant Engineer in India, and as a Research Fellow on an EPSRC/industry project at Queen’s University of Belfast, UK.
His research focuses on the development of sustainable intelligent systems that leverage computational intelligence to address complex challenges in healthcare, industry, and critical infrastructure. By integrating machine learning, neural and fuzzy systems, evolutionary optimisation, online just-in-time adaptive learning, predictive modelling, and advanced control, he develops methods for modelling, monitoring, optimising, and controlling nonlinear, uncertain, and time-varying systems. His research spans computational intelligence, data engineering, quantum machine learning, brain modelling, brain–computer interfaces, neurorehabilitation, assistive technologies, and intelligent cyber-physical systems. His overarching goal is to deliver sustainable societal and economic impact through improved healthcare accessibility, enhanced quality of life, energy-efficient and resilient infrastructure, reduced environmental footprint in industrial operations, and next-generation smart manufacturing systems that support responsible production and sustainable development.
Under his supervision, an advanced rehabilitation protocol has been developed incorporating an active physical practice stage followed by a mental practice stage, using a neuro-rehab system consisting of a robotic hand exoskeleton and an EEG/MEG based BCI, which has been trialled on groups of chronic stroke patients in UK as well as India, resulting in transformative change in patients’ quality of life. He has published over 315 research papers in journals, edited books, and conference proceedings. He has supervised to completion 25 PhD students. His research has attracted 28 research grant awards amounting to over £16M funding from national and international agencies including Invest Northern Ireland, Department of Employment and Learning, Research Councils UK (RCUK), Leverhulme Trust, Royal Society, UK India Education and Research Initiative (UKIERI), UK Research and Innovation (UKRI) and Irish industry.
Employment
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University of Ulster Professor of Intelligent Systems1999 - Present
Education
- 1993 - 1997
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Indian Institute of Technology Roorkee MTech (Computer Science & Technology)1988 - 1990
- 1982 - 1986
Projects & Funding
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Semiconductor Photonics Education and Research (SPEAR) Centre Special EU Programmes Body (SEUPB) for managing funding under the PEACEPLUS, PEACE IV and INTERREG VA Programmes2025 - 2029
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Health Frontiers – Technology Innovation Centre (HF-TIC) Special EU Programmes Body (SEUPB) for managing funding under the PEACEPLUS, PEACE IV and INTERREG VA Programmes2025 - 2029
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Upgrading Magnetoencephalography (MEG) system with Internal Helium Recycler (IHR) Medical Research Council2022 - 2023
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Smart Nano-Manufacturing Corridor UK Research and Innovation2021 - 2027
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Advancing MEG based Brain-Computer Interface Supported Upper Limb Post-Stroke Rehabilitation British Council2017 - 2020
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EpiFASSTT: Epigenetic effects on children's psychosocial development in a randomised trial of Folic Acid Supplementation in Second and Third Trimester Economic and Social Research Council2016 - 2019
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To develop a performance monitoring and optimisation system for efficient operation of land-fill site electricity generators. Innovate UK2012 - 2015
Publications (343)
- Data-driven cycle time optimisation in semiconductor manufacturing using machine learning and heuristic search algorithms Save
- Unsupervised feature learning and optimised clustering with fine-tuning for automatic semiconductor wafer defect recognition Save
- Comparative performance analysis of quantum feature maps for quantum kernel-based machine learning Save
- A Spiking Neural Network-Quantum Model for Spatiotemporal Data Analysis: An Experimental Framework Save
- Data-Driven Cycle Time Optimisation in Semiconductor Manufacturing Using Machine Learning and Heuristic Search Algorithms Save
- A hybrid spiking neural network - quantum framework for spatio-temporal data classification: a case study on EEG data Save
- Health Monitoring and Drift Detection of Bearing Using Direct Density Ratio Estimation Save
- Neurophysiological Fluctuation Detects Mental Fatigue Prior to Subjective Awareness Save
- Estimation of Interferences in Magnetoencephalography (MEG) Brain Data Using Intelligent Methods for BCI-based Neurorehabilitation Applications Save
- Machine Learning with Heuristic Search-based Hybrid Framework for Cycle Time Optimization in Semiconductor Production Save
- Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data Save
- A Hybrid Spiking Neural Network-Quantum Classifier Framework: A Case Study Using EEG Data Save
- Visual Angles and Emotional Valence Affect Temporal Dynamics of Neural Representations of Facial Expression: An MEG Study Save
- A Hybrid RNN-CNN based Motor Imagery Tasks Classification Approach Using MEG Brain Signals for BCI Applications Save
- IMPACT OF MENTAL FATIGUE ON REGAINING MOTOR FUNCTIONALITY: A PRELIMINARY EEG STUDY ON STROKE SURVIVORS Save
- Dynamic source localization and functional connectivity estimation with multiple penalized state-space models Save
- Quantum-Enhanced Feature Maps for Improved Quantum Kernels and Advanced Quantum Machine Learning Application Save
- An Automated Detection of Amyotrophic Lateral Sclerosis from Resting State MEG Data Using 3D Deep Convolutional Neural Network Save
- A Two-Step Framework for Predictive Maintenance of Cryogenic Pumps in Semiconductor Manufacturing Save
- Efficient Wafer Defect Patterns Recognition Using Deep Convolutional Neural Network Save