World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6197
World Ranking
10712
National Ranking
323

Overview

John Yearwood is affiliated with Deakin University in Australia and has contributed extensively to the field of computer science. Their publication record includes at least 53 works, with a significant focus on artificial intelligence, plant science, cardiology, biomedical engineering, and cognitive neuroscience.

Their research spans various subfields, notably:

  • Artificial Intelligence
  • Plant Science
  • Cardiology and Cardiovascular Medicine
  • Biomedical Engineering
  • Cognitive Neuroscience

Key topics addressed in their work include:

  • ECG Monitoring and Analysis
  • Smart Agriculture and AI
  • EEG and Brain-Computer Interfaces
  • Non-Invasive Vital Sign Monitoring
  • Privacy-Preserving Technologies in Data
  • Plant Disease Management Techniques
  • Emotion and Mood Recognition

Yearwood has published frequently in several venues, with multiple papers appearing in:

  • arXiv (Cornell University)
  • Knowledge-Based Systems
  • IEEE Access
  • Information Sciences
  • Computers, materials & continua/Computers, materials & continua (Print)

Frequent collaborators include:

  • Sutharshan Rajasegarar
  • Selvarajah Thuseethan
  • Chandan Karmakar
  • Sivasubramaniam Janarthan
  • Ahsan Habib

Recent papers published by Yearwood include:

  • "Blockchain-enabled Federated Learning: A Survey," 2022, ACM Computing Surveys
  • "Deep Metric Learning Based Citrus Disease Classification With Sparse Data," 2020, IEEE Access
  • "Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning," 2020, Translational Psychiatry
  • "Robustness of electrocardiogram signal quality indices," 2022, Journal of The Royal Society Interface
  • "LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions," 2020, Knowledge-Based Systems

Best Publications

  • Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.

    Wei Luo;Dinh Phung;Truyen Tran;Sunil Gupta

  • Cayley graphs as classifiers for data mining: The influence of asymmetries

    Andrei Kelarev;Joe Ryan;John Yearwood

  • Blockchain-enabled Federated Learning: A Survey

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  • A hybrid feature selection with ensemble classification for imbalanced healthcare data: A case study for brain tumor diagnosis

    Shamsul Huda;John Yearwood;Herbert F. Jelinek;Mohammad Mehedi Hassan

  • An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling

    Adil M. Bagirov;A. F. Barton;H. Mala-Jetmarova;A. Al Nuaimat

  • A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems

    Adil M. Bagirov;John Yearwood

  • Unsupervised and supervised data classification via nonsmooth and global optimization

    A. M. Bagirov;A. M. Rubinov;N. V. Soukhoroukova;J. Yearwood

  • Hybrids of support vector machine wrapper and filter based framework for malware detection

    Shamsul Huda;Jemal Abawajy;Mamoun Alazab;Mali Abdollalihian

  • Heterogeneous Cooperative Co-Evolution Memetic Differential Evolution Algorithm for Big Data Optimization Problems

    Nasser R. Sabar;Jemal Abawajy;John Yearwood

  • On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts

    Peter Vamplew;John Yearwood;Richard Dazeley;Adam Berry

  • Protection of Privacy in Biometric Data

    Iynkaran Natgunanathan;Abid Mehmood;Yong Xiang;Gleb Beliakov

  • Detection of epileptic seizure based on entropy analysis of short-term EEG.

    Peng Li;Chandan Karmakar;Chandan Karmakar;John Yearwood;Svetha Venkatesh

  • Securing the operations in SCADA-IoT platform based industrial control system using ensemble of deep belief networks

    Shamsul Huda;John Yearwood;Mohammad Mehedi Hassan;Ahmad Almogren

  • Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabeled data

    Shamsul Huda;Suruz Miah;Mohammad Mehedi Hassan;Rafiqul Islam

  • Does the Delphi process lead to increased accuracy in group-based judgmental forecasts or does it simply induce consensus amongst judgmental forecasters ?

    Fergus Bolger;Andrew Stranieri;George Wright;John Yearwood

  • New algorithms for multi-class cancer diagnosis using tumor gene expression signatures

    Adil M. Bagirov;Brent Ferguson;Sasha Ivkovic;G. Saunders

  • A Framework for Software Defect Prediction and Metric Selection

    Shamsul Huda;Sultan Alyahya;Mohsin Ali;Shafiq Ahmad

  • Predicting Australian stock market index using neural networks exploiting dynamical swings and intermarket influences

    Heping Pan;Chandima Tilakaratne;John Leighton Yearwood

  • Deep metric learning based citrus disease classification with sparse data

    Sivasubramaniam Janarthan;Selvarajah Thuseethan;Sutharshan Rajasegarar;Qiang Lyu

  • A Global Optimization Approach to Classification

    Adil M. Bagirov;Alexander M. Rubinov;John Yearwood

  • Consensus clustering and supervised classification for profiling phishing emails in internet commerce security

    Richard Dazeley;John L. Yearwood;Byeong H. Kang;Andrei V. Kelarev

  • Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabelled data

    Rafiqul Islam;Shamsul Huda;Mohammad Mehedi Hassan;Suruz Miah

Frequent Co-Authors

Jemal H. Abawajy
Jemal H. Abawajy Deakin University
Paul A. Watters
Paul A. Watters La Trobe University
Sutharshan Rajasegarar
Sutharshan Rajasegarar Deakin University
Gleb Beliakov
Gleb Beliakov Deakin University
Svetha Venkatesh
Svetha Venkatesh Deakin University
Dinh Phung
Dinh Phung Monash University
Mohammad Mehedi Hassan
Mohammad Mehedi Hassan King Saud University
Yong Xiang
Yong Xiang Deakin University
Mamoun Alazab
Mamoun Alazab Charles Darwin University
Helen Christensen
Helen Christensen University of New South Wales

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Related Online Degrees & Career Pathways

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