World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
11861
World Ranking
6371
National Ranking
382

Overview

Richard M. Everson is affiliated with the University of Exeter in the United Kingdom. Their research output spans multiple fields with a focus on medicine and engineering, reflecting diverse academic interests and expertise.

Their recent publications cover a range of topics and venues, illustrating a cross-disciplinary approach. Some recent papers include:

  • Greed Is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation, 2021, ACM Transactions on Evolutionary Learning and Optimization
  • Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients, 2021, JAMA Network Open
  • C3-IoC: A Career Guidance System for Assessing Student Skills using Machine Learning and Network Visualisation, 2022, International Journal of Artificial Intelligence in Education
  • Shape optimisation of the sharp-heeled Kaplan draft tube: Performance evaluation using Computational Fluid Dynamics, 2020, Renewable Energy
  • Using computational techniques to study social influence online, 2020, Group Processes & Intergroup Relations

Frequent co-authors collaborating with Richard M. Everson include:

  • George De Ath
  • Jonathan E. Fieldsend
  • Maya Harary
  • Joshua Casaos
  • Jérémie Vitte

Richard M. Everson's work has been published repeatedly in several key venues, indicating areas of sustained research interest:

  • Neuro-Oncology
  • Alzheimer s & Dementia
  • arXiv (Cornell University)
  • Journal of Neurological Surgery Part B Skull Base
  • bioRxiv (Cold Spring Harbor Laboratory)

The main fields of study for Richard M. Everson are Medicine and Engineering. Subfields with significant contributions include:

  • Artificial Intelligence
  • Aerospace Engineering
  • Epidemiology
  • Ophthalmology
  • Management Science and Operations Research

The scientist's research topics cover a variety of advanced and applied areas such as:

  • Advanced Multi-Objective Optimization Algorithms
  • Acute Ischemic Stroke Management
  • Advanced Bandit Algorithms Research
  • Aerospace and Aviation Technology
  • Air Traffic Management and Optimization
  • Autonomous Vehicle Technology and Safety
  • Water Systems and Optimization

Best Publications

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • Surface roughness analysis, modelling and prediction in selective laser melting

    Giovanni Strano;Liang Hao;Richard M. Everson;Kenneth E. Evans

  • Karhunen–Loève procedure for gappy data

    R. Everson;L. Sirovich

  • The sixth visual object tracking VOT2018 challenge results

    Matej Kristan;Aleš Leonardis;Jiří Matas;Michael Felsberg

  • Advanced lattice support structures for metal additive manufacturing

    Ahmed Hussein;Liang Hao;Chunze Yan;Richard Everson

  • A new approach to the design and optimisation of support structures in additive manufacturing.

    Giorgio Strano;L. Hao;R. Everson;K. Evans

  • The Seventh Visual Object Tracking VOT2019 Challenge Results

    Matej Kristan;Amanda Berg;Linyu Zheng;Litu Rout

  • Independent Component Analysis: Principles and Practice

    Stephen Roberts;Richard Everson

  • Weakly Supervised Joint Sentiment-Topic Detection from Text

    Chenghua Lin;Yulan He;R. Everson;S. Ruger

  • A MOPSO algorithm based exclusively on pareto dominance concepts

    Julio E. Alvarez-Benitez;Richard M. Everson;Jonathan E. Fieldsend

  • Using unconstrained elite archives for multiobjective optimization

    J.E. Fieldsend;R.M. Everson;S. Singh

  • Dominance-Based Multiobjective Simulated Annealing

    K.I. Smith;R.M. Everson;J.E. Fieldsend;C. Murphy

  • Representation of spatial frequency and orientation in the visual cortex

    R. M. Everson;A. K. Prashanth;M. Gabbay;B. W. Knight

  • Visualizing Mutually Nondominating Solution Sets in Many-Objective Optimization

    D. J. Walker;R. M. Everson;J. E. Fieldsend

  • Multi-class ROC analysis from a multi-objective optimisation perspective

    Richard M. Everson;Jonathan E. Fieldsend

  • Management and Analysis of Large Scientific Datasets

    Lawrence Sirovich;Richard Everson

  • Dominance measures for multi-objective simulated annealing

    K.I. Smith;R.M. Everson;J.E. Fieldsend

  • Wavelet analysis of the turbulent jet

    R. Everson;L. Sirovich;K.R. Sreenivasan

  • An empirical analysis of the probabilistic K-nearest neighbour classifier

    S. Manocha;M. A. Girolami

  • Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation

    George De Ath;Richard M. Everson;Alma A. M. Rahat;Jonathan E. Fieldsend

  • Intelligent Data Engineering and Automated Learning – IDEAL 2004

    Zheng Rong Yang;Hujun Yin;Richard M. Everson

  • Maximum certainty data partitioning

    Stephen J. Roberts;Richard M. Everson;Iead Rezek

Frequent Co-Authors

Stephen J. Roberts
Stephen J. Roberts University of Oxford
Lawrence Sirovich
Lawrence Sirovich Brown University
Liang Hao
Liang Hao Institute of Applied Physics and Computational Mathematics
Zoran Kapelan
Zoran Kapelan Delft University of Technology
William D. Penny
William D. Penny University of East Anglia
Tom Vercauteren
Tom Vercauteren King's College London
Kenneth E. Evans
Kenneth E. Evans University of Exeter
David J. Llewellyn
David J. Llewellyn University of Exeter
Murray Grant
Murray Grant University of Warwick
Arlindo L. Oliveira
Arlindo L. Oliveira University of Lisbon

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