World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7290
World Ranking
8400
National Ranking
3597

Lee Spector 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 Lee Spector 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: 211 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

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

Lee Spector 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 Lee Spector 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Lee Spector is affiliated with Hampshire College in the United States and has a significant research presence in the fields of Computer Science and Biochemistry, Genetics and Molecular Biology. Their work spans multiple subfields, primarily focusing on Artificial Intelligence and Molecular Biology, along with areas such as Computer Science Applications, Genetics, and Information Systems.

Their main research topics include Evolutionary Algorithms and Applications, Metaheuristic Optimization Algorithms Research, and Teaching and Learning Programming. Other areas of interest encompassed Reinforcement Learning in Robotics, Viral Infectious Diseases and Gene Expression in Insects, Machine Learning in Bioinformatics, and Evolution and Genetic Dynamics.

Lee Spector's recent publications reflect these interests, including:

  • On the importance of specialists for lexicase selection, 2020, Genetic Programming and Evolvable Machines
  • Evolutionary quantum architecture search for parametrized quantum circuits, 2022, Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Multi-Objective Evolutionary Architecture Search for Parameterized Quantum Circuits, 2023, Entropy
  • Lexicase selection at scale, 2022, Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Informed Down-Sampled Lexicase Selection: Identifying Productive Training Cases for Efficient Problem Solving, 2024, Evolutionary Computation

Lee Spector frequently collaborates with other researchers in their field. Notable coauthors include Thomas Helmuth, Ryan Boldi, Li Ding, Edward Pantridge, and Alexander Lalejini. These collaborations have contributed to their publications in various academic venues.

Regarding publication venues, Lee Spector has a strong record of contributions to:

  • arXiv (Cornell University)
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Genetic Programming and Evolvable Machines
  • Proceedings of the Genetic and Evolutionary Computation Conference
  • Entropy

Best Publications

  • Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations

    C. Muro;R. Escobedo;L. Spector;R.P. Coppinger

  • Ontology-based Web agents

    Sean Luke;Lee Spector;David Rager;James Hendler

  • Genetic Programming and Autoconstructive Evolution with the Push Programming Language

    Lee Spector;Alan Robinson

  • Evolving teamwork and coordination with genetic programming

    Sean Luke;Lee Spector

  • Solving Uncompromising Problems With Lexicase Selection

    Thomas Helmuth;Lee Spector;James Matheson

  • Emergence of Collective Behavior in Evolving Populations of Flying Agents

    Lee Spector;Jon Klein;Chris Perry;Mark Feinstein

  • Automatic Quantum Computer Programming: A Genetic Programming Approach

    Lee C. Spector

  • General Program Synthesis Benchmark Suite

    Thomas Helmuth;Lee Spector

  • The Push3 execution stack and the evolution of control

    Lee Spector;Jon Klein;Maarten Keijzer

  • A Comparison of Crossover and Mutation in Genetic Programming

    Sean Luke;Lee Spector

  • Assessment of problem modality by differential performance of lexicase selection in genetic programming: a preliminary report

    Lee Spector

  • Epsilon-Lexicase Selection for Regression

    William La Cava;Lee Spector;Kourosh Danai

  • Quantum computing applications of genetic programming

    Lee Spector;Howard Barnum;Herbert J. Bernstein;Nikhil Swamy

  • Open-ended evolution: Perspectives from the oee workshop in york

    Tim Taylor;Mark Bedau;Alastair Channon;David Ackley

  • Finding a better-than-classical quantum AND/OR algorithm using genetic programming

    L. Spector;H. Barnum;H.J. Bernstein;N. Swamy

  • Ontology-Based Knowledge Discovery on the World-Wide Web

    Sean Luke;Lee Spector;David Rager

  • Defining and simulating open-ended novelty: requirements, guidelines, and challenges.

    Wolfgang Banzhaf;Bert Baumgaertner;Guillaume Beslon;René Doursat

  • Autoconstructive Evolution: Push, PushGP, and Pushpop

    Lee Spector

  • Evolution of artificial intelligence

    Lee Spector

  • Simultaneous evolution of programs and their control structures

    Lee Spector

  • Criticism, culture, and the automatic generation of artworks

    Lee Spector;Adam Alpern

  • Genetic and Evolutionary Computation – GECCO 2004

    Unknown

  • Multi-type, Self-adaptive Genetic Programming as an Agent Creation Tool

    Lee Spector

Frequent Co-Authors

James A. Hendler
James A. Hendler Rensselaer Polytechnic Institute
Howard Barnum
Howard Barnum University of New Mexico
Sean Luke
Sean Luke George Mason University
Jason H. Moore
Jason H. Moore University of Pennsylvania
Sara Silva
Sara Silva University of Lisbon
Leonardo Vanneschi
Leonardo Vanneschi Universidade Nova de Lisboa
Matthew A. Lackner
Matthew A. Lackner University of Massachusetts Amherst
Paul Fleming
Paul Fleming National Renewable Energy Laboratory
Jordan Grafman
Jordan Grafman Northwestern University

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