World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
6992
World Ranking
8434
National Ranking
513

Overview

Girijesh Prasad is affiliated with the University of Ulster in the United Kingdom. Their research primarily focuses on neuroscience and medicine, with a strong emphasis on cognitive neuroscience and applications of artificial intelligence. The work engages deeply with EEG and brain-computer interface technologies, neural dynamics, and functional brain connectivity studies.

The scientist's publication record includes contributions to topics such as:

  • EEG and Brain-Computer Interfaces
  • Functional Brain Connectivity Studies
  • Neural dynamics and brain function
  • Dementia and Cognitive Impairment Research
  • Neuroscience and Neural Engineering
  • Gaze Tracking and Assistive Technology
  • Machine Learning in Healthcare

Prasad has published extensively in fields closely related to neuroscience with 59 publications, and medicine with 27 publications. Their subfields of study include cognitive neuroscience, artificial intelligence, psychiatry and mental health, electrical and electronic engineering, and cellular and molecular neuroscience.

The scientist's recent papers include:

  • "An automatic subject specific channel selection method for enhancing motor imagery classification in EEG-BCI using correlation" (2021), published in Biomedical Signal Processing and Control
  • "Effects of maternal folic acid supplementation during the second and third trimesters of pregnancy on neurocognitive development in the child: an 11-year follow-up from a randomised controlled trial" (2021), published in BMC Medicine
  • "Deep Learning Based Inter-subject Continuous Decoding of Motor Imagery for Practical Brain-Computer Interfaces" (2020), published in Frontiers in Neuroscience
  • "Neurofeedback with low-cost, wearable electroencephalography (EEG) reduces symptoms in chronic Post-Traumatic Stress Disorder" (2021), published in Journal of Affective Disorders
  • "Assessing impact of channel selection on decoding of motor and cognitive imagery from MEG data" (2020), published in Journal of Neural Engineering

The frequent co-authors collaborating with Girijesh Prasad include:

  • KongFatt Wong-Lin
  • Niamh McCombe
  • Paula L. McClean
  • David P. Finn
  • Stephen Todd

Publications have appeared repeatedly in venues such as bioRxiv (Cold Spring Harbor Laboratory), Multimedia Tools and Applications, arXiv (Cornell University), Annual Conference of the PHM Society, and Biomedical Signal Processing and Control.

Best Publications

  • Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study

    Girijesh Prasad;Pawel Herman;Damien Coyle;Suzanne McDonough

  • Comparative Analysis of Spectral Approaches to Feature Extraction for EEG-Based Motor Imagery Classification

    P. Herman;G. Prasad;T.M. McGinnity;D. Coyle

  • An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network

    Gang Leng;Thomas Martin McGinnity;Girijesh Prasad

  • An on-line algorithm for creating self-organizing fuzzy neural networks

    Gang Leng;Girijesh Prasad;Thomas Martin McGinnity

  • A Multi-class EEG-based BCI classification using Multivariate Empirical Mode Decomposition Based Filtering and Riemannian Geometry

    Pramod Gaur;Ram Bilas Pachori;Hui Wang;Girijesh Prasad

  • Design for Self-Organizing Fuzzy Neural Networks Based on Genetic Algorithms

    Gang Leng;T.M. McGinnity;G. Prasad

  • Statistical and computational intelligence techniques for inferential model development: a comparative evaluation and a novel proposition for fusion

    K. Warne;G. Prasad;S. Rezvani;L. Maguire

  • Quantum Neural Network-Based EEG Filtering for a Brain–Computer Interface

    Vaibhav Gandhi;Girijesh Prasad;Damien Coyle;Laxmidhar Behera

  • Electrophysiological signatures of intentional social coordination in the 10–12 Hz range

    Muhammad Naeem;Girijesh Prasad;David R. Watson;J.A. Scott Kelso;J.A. Scott Kelso

  • A time-series prediction approach for feature extraction in a brain-computer interface

    D. Coyle;G. Prasad;T.M. McGinnity

  • EEG-Based Mobile Robot Control Through an Adaptive Brain–Robot Interface

    Vaibhav Gandhi;Girijesh Prasad;Damien Coyle;Laxmidhar Behera

  • A Local Model Networks Based Multivariable Long-Range Predictive Control Strategy for Thermal Power Plants

    G. Prasad;E. Swidenbank;B. W. Hogg

  • EWMA model based shift-detection methods for detecting covariate shifts in non-stationary environments

    Haider Raza;Girijesh Prasad;Yuhua Li

  • Adaptive learning with covariate shift-detection for motor imagery-based brain---computer interface

    Haider Raza;Hubert Cecotti;Yuhua Li;Girijesh Prasad

  • A neural net model-based multivariable long-range predictive control strategy applied in thermal power plant control

    G. Prasad;E. Swidenbank;B.W. Hogg

  • Faster Self-Organizing Fuzzy Neural Network Training and a Hyperparameter Analysis for a Brain–Computer Interface

    D. Coyle;G. Prasad;T.M. McGinnity

  • M/EEG-Based Bio-Markers to Predict the MCI and Alzheimer's Disease: A Review From the ML Perspective

    Su Yang;Jose Miguel Sanchez Bornot;Kongfatt Wong-Lin;Girijesh Prasad

  • An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface

    Pramod Gaur;Ram Bilas Pachori;Hui Wang;Girijesh Prasad

  • A practical computerized decision support system for predicting the severity of Alzheimer's disease of an individual.

    Magda Bucholc;Xuemei Ding;Haiying;HY Wang

  • Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface

    Haider Raza;Dheeraj Rathee;Shang-Ming Zhou;Hubert Cecotti

  • An empirical mode decomposition based filtering method for classification of motor-imagery EEG signals for enhancing brain-computer interface

    Pramod Gaur;Ram Bilas Pachori;Hui Wang;Girijesh Prasad

  • A time-frequency approach to feature extraction for a brain-computer interface with a comparative analysis of performance measures

    Damien Coyle;Girijesh Prasad;T. M. McGinnity

  • Bispectrum-based feature extraction technique for devising a practical brain?computer interface

    Shahjahan Shahid;Girijesh Prasad

Frequent Co-Authors

TM McGinnity
TM McGinnity University of Ulster
Damien Coyle
Damien Coyle University of Ulster
Liam Maguire
Liam Maguire University of Ulster
Laxmidhar Behera
Laxmidhar Behera Indian Institute of Technology Kanpur
David P. Finn
David P. Finn University of Galway
Ram Bilas Pachori
Ram Bilas Pachori Indian Institute of Technology Indore
J. A. Scott Kelso
J. A. Scott Kelso Florida Atlantic University
George W. Irwin
George W. Irwin Queen's University Belfast
Kevin Curran
Kevin Curran University of Ulster
Fernando Maestú
Fernando Maestú Complutense University of Madrid

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