World's Best Scientists 2026 revealed!
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Computer Science
USA
2025

D-Index & Metrics

Computer Science

D-Index
115
Citations
301272
World Ranking
182
National Ranking
106

Research.com Recognitions

  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2010 - Evolutionary Computation Pioneer Award, IEEE Computational Intelligence Society

Overview

David E. Goldberg is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research spans multiple fields of study, focusing primarily on Psychology and Neuroscience, with specific attention to Developmental and Educational Psychology, Cognitive Neuroscience, and General Psychology.

The main topics covered in their work include Educational and Psychological Assessments, Neuroscience, Education and Cognitive Function, and Academic and Historical Perspectives in Psychology.

Their recent publication includes the paper titled Remembering Jeffrey Horn (1963-2024), published in 2024 in ACM SIGEVOlution.

  • Nina Jirouskova
  • Kalyanmoy Deb
  • William B. Langdon

  • ACM SIGEVOlution

David E. Goldberg has authored books published by Fordham University Press eBooks, including The Retreats of Reconstruction, released in 2020.

In 2010, they were recognized with the Evolutionary Computation Pioneer Award from the IEEE Computational Intelligence Society.

Best Publications

  • Genetic algorithms in search, optimization, and machine learning

    David E. Goldberg

  • Genetic Algorithms

    D E Goldberg;William Shakespeare

  • Genetic Algorithms in Search

    D. E. Goldberg

  • Using collaborative filtering to weave an information tapestry

    David Goldberg;David Nichols;Brian M. Oki;Douglas Terry

  • Genetic Algorithms and Machine Learning

    David E. Goldberg;John H. Holland

  • A niched Pareto genetic algorithm for multiobjective optimization

    J. Horn;N. Nafpliotis;D.E. Goldberg

  • A Comparative Analysis of Selection Schemes Used in Genetic Algorithms

    David E. Goldberg;Kalyanmoy Deb

  • Genetic algorithms with sharing for multimodal function optimization

    David E. Goldberg;Jon Richardson

  • What every computer scientist should know about floating-point arithmetic

    David Goldberg

  • Genetic Algorithms in Search, Optimization & Machine Learning

    D. E. Goldberg

  • Alleles, loci and the traveling salesman problem

    D. E. Goldberg

  • A Survey of Optimization by Building and Using Probabilistic Models

    Martin Pelikan;David E. Goldberg;Fernando G. Lobo

  • Messy genetic algorithms: motivation, analysis, and first results

    David E. Goldberg;Bradley Korb;Kalyanmoy Deb

  • The compact genetic algorithm

    G.R. Harik;F.G. Lobo;D.E. Goldberg

  • The Design of Innovation: Lessons from and for Competent Genetic Algorithms

    David E. Goldberg

  • Classifier systems and genetic algorithms

    L. B. Booker;D. E. Goldberg;J. H. Holland

  • Genetic Algorithms, Tournament Selection, and the Effects of Noise.

    Brad L. Miller;David E. Goldberg

  • An Investigation of Niche and Species Formation in Genetic Function Optimization

    Kalyanmoy Deb;David E. Goldberg

  • BOA: the Bayesian optimization algorithm

    Martin Pelikan;David E. Goldberg;Erick Cantú-Paz

  • Genetic Algorithm in Search

    D. E. Goldberg

Frequent Co-Authors

Kumara Sastry
Kumara Sastry University of Illinois at Urbana-Champaign
Martin Pelikan
Martin Pelikan University of Missouri
Martin V. Butz
Martin V. Butz University of Tübingen
Pier Luca Lanzi
Pier Luca Lanzi Polytechnic University of Milan
Kalyanmoy Deb
Kalyanmoy Deb Michigan State University
Barbara S. Minsker
Barbara S. Minsker Southern Methodist University
Erick Cantú-Paz
Erick Cantú-Paz Amazon (United States)
Stewart W. Wilson
Stewart W. Wilson University of Illinois at Urbana-Champaign
Duane D. Johnson
Duane D. Johnson Iowa State University
Patrick M. Reed
Patrick M. Reed Cornell University

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