World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
5446
World Ranking
11271
National Ranking
4654

Robert G. Reynolds publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Robert G. Reynolds sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 315 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Robert G. Reynolds D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Robert G. Reynolds sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Robert G. Reynolds is affiliated with Wayne State University in the United States. Their research spans multiple disciplines, primarily within Computer Science and Mathematics, with 28 publications in Computer Science and 18 in Mathematics.

Their work frequently focuses on Artificial Intelligence, Applied Mathematics, and Algebra and Number Theory. More specific subfields include Computer Vision and Pattern Recognition and Computational Mechanics.

Key topics addressed in their research are:

  • Mathematical functions and polynomials
  • Advanced Mathematical Identities
  • Evolutionary Algorithms and Applications
  • Metaheuristic Optimization Algorithms Research
  • Reinforcement Learning in Robotics
  • Artificial Intelligence in Games
  • Astronomical Observations and Instrumentation

Recent papers by Robert G. Reynolds include:

  • Evaluation of fan-beam kilovoltage computed tomography image quality on a novel biological-guided radiotherapy platform, 2023, Physics and Imaging in Radiation Oncology
  • Evolving Deep Neural Networks with Cultural Algorithms for Real-Time Industrial Applications, 2022, International Journal of Semantic Computing
  • Cultural Algorithms as a Framework for the Design of Trustable Evolutionary Algorithms, 2022, International Journal of Semantic Computing
  • Learning the Impact of Group Structure on Optimal Herd Path Planning with Cultural Algorithms, 2022, 2022 IEEE Congress on Evolutionary Computation (CEC)
  • Cultural Algorithm Guided Policy Gradient with Parameter Exploration, 2024, Proceedings of the AAAI Symposium Series

Frequent co-authors collaborating with Reynolds are:

  • Thomas Palazzolo
  • Chencheng Zhang
  • Sarah Saad
  • A D Stauffer
  • Ashley Lemke

Publication venues where Reynolds has contributed multiple works include:

  • arXiv (Cornell University)
  • International Journal of Semantic Computing
  • 2022 IEEE Congress on Evolutionary Computation (CEC)
  • Physics and Imaging in Radiation Oncology
  • Proceedings of the AAAI Symposium Series

Best Publications

  • Using knowledge-based evolutionary computation to solve nonlinear constraint optimization problems: a cultural algorithm approach

    Xidong Jin;R.G. Reynolds

  • An ensemble sinusoidal parameter adaptation incorporated with L-SHADE for solving CEC2014 benchmark problems

    Noor H. Awad;Mostafa Z. Ali;Ponnuthurai N. Suganthan;Robert G. Reynolds

  • Simulating ancient societies.

    Timothy A. Kohler;George J. Gumerman;Robert G. Reynolds

  • An Adaptive Multipopulation Differential Evolution With Dynamic Population Reduction

    Mostafa Z. Ali;Noor H. Awad;Ponnuthurai Nagaratnam Suganthan;Robert G. Reynolds

  • A Testbed for Solving Optimization Problems Using Cultural Algorithms.

    Chan-Jin Chung;Robert G. Reynolds

  • CAEP: AN EVOLUTION-BASED TOOL FOR REAL-VALUED FUNCTION OPTIMIZATION USING CULTURAL ALGORITHMS

    Chan-Jin Chung;Robert G. Reynolds

  • Cultural algorithms: theory and applications

    Robert G. Reynolds

  • Knowledge-based function optimization using fuzzy cultural algorithms with evolutionary programming

    R.G. Reynolds;Shinin Zhu

  • Evolutionary Programming VI

    Peter J. Angeline;Robert G. Reynolds;John R. McDonnell;Russ Eberhart

  • Cultural algorithms: modeling of how cultures learn to solve problems

    R.G. Reynolds;B. Peng

  • Using Cultural Algorithms for Constraint Handling in GENOCOP

    John R. McDonnell;Robert G. Reynolds;David B. Fogel

  • Knowledge-based self-adaptation in evolutionary programming using cultural algorithms

    R.G. Reynolds;ChanJin Chung

  • Docking Conformationally Flexible Small Molecules into a Protein Binding Site Through Evolutionary Programming

    John R. McDonnell;Robert G. Reynolds;David B. Fogel

  • Problem solving using cultural algorithms

    R.G. Reynolds;W. Sverdlik

  • The WCCI 2008 simulated car racing competition

    D. Loiacono;J. Togelius;P.L. Lanzi;L. Kinnaird-Heether

  • An improved class of real-coded Genetic Algorithms for numerical optimization✰

    Mostafa Z. Ali;Noor H. Awad;Ponnuthurai N. Suganthan;Ali M. Shatnawi

  • Using cultural algorithms to support re-engineering of rule-based expert systems in dynamic performance environments: a case study in fraud detection

    M. Sternberg;R.G. Reynolds

  • A self-adaptive approach to representation shifts in cultural algorithms

    R.G. Reynolds;ChanJin Chung

  • Knowledge-based solution to dynamic optimization problems using cultural algorithms

    Robert G. Reynolds;Saleh M. Saleem

  • An Evolutionary Programming Approach To Self-Adaptation On Finite State Machines

    John R. McDonnell;Robert G. Reynolds;David B. Fogel

  • Evolutionary computation: Towards a new philosophy of machine intelligence

    Robert G. Reynolds

Frequent Co-Authors

David B. Fogel
David B. Fogel Torrey Pines Institute For Molecular Studies
Jonathan I. Maletic
Jonathan I. Maletic Kent State University
Joyce Marcus
Joyce Marcus University of Michigan–Ann Arbor
Kent V. Flannery
Kent V. Flannery University of Michigan–Ann Arbor
Shiyong Lu
Shiyong Lu Wayne State University
Julian Togelius
Julian Togelius New York University
Karl R. Stapelfeldt
Karl R. Stapelfeldt Jet Propulsion Lab
Bernard P. Zeigler
Bernard P. Zeigler University of Arizona
Michael F. Skrutskie
Michael F. Skrutskie University of Virginia

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