World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
9266
World Ranking
7147
National Ranking
228

Tapabrata Ray 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 Tapabrata Ray 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: 287 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Tapabrata Ray 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 Tapabrata Ray 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Tapabrata Ray is affiliated with the University of New South Wales in Australia. Their research spans across computer science and engineering, with a focus on optimization algorithms and engineering design.

Their main fields of study include:

  • Computer Science
  • Engineering

Within these fields, Tapabrata Ray has concentrated on several subfields such as:

  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Electrical and Electronic Engineering

Their primary research topics cover:

  • Advanced Multi-Objective Optimization Algorithms
  • Metaheuristic Optimization Algorithms Research
  • Probabilistic and Robust Engineering Design
  • Topology Optimization in Engineering
  • Optimal Experimental Design Methods
  • Evolutionary Algorithms and Applications
  • Transportation and Mobility Innovations

Tapabrata Ray has contributed to multiple recent papers, including:

  • Partial Evaluation Strategies for Expensive Evolutionary Constrained Optimization (2021), published in IEEE Transactions on Evolutionary Computation
  • The road to the ideal stent: A review of stent design optimisation methods, findings, and opportunities (2023), published in Materials & Design
  • Real-time scheduling of community microgrid (2020), published in Journal of Cleaner Production
  • An efficient optimization approach for flexibility provisioning in community microgrids with an incentive-based demand response scheme (2021), published in Sustainable Cities and Society
  • EV Hosting Capacity Enhancement in a Community Microgrid Through Dynamic Price Optimization-Based Demand Response (2022), published in IEEE Transactions on Cybernetics

Their research outputs have appeared frequently in notable venues such as:

  • Proceedings of the Genetic and Evolutionary Computation Conference
  • IEEE Transactions on Evolutionary Computation
  • Swarm and Evolutionary Computation
  • arXiv (Cornell University)
  • Journal of Mechanical Design

Tapabrata Ray has collaborated extensively with several coauthors, including:

  • Hemant Kumar Singh
  • Angus Kenny
  • Kamrul Hasan Rahi
  • Nigel Jepson
  • Susann Beier

Best Publications

  • Society and civilization: An optimization algorithm based on the simulation of social behavior

    T. Ray;K.M. Liew

  • A Swarm Metaphor for Multiobjective Design Optimization

    Tapabrata Ray;K.M. Liew

  • A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization

    M. Asafuddoula;Tapabrata Ray;Ruhul Sarker

  • ENGINEERING DESIGN OPTIMIZATION USING A SWARM WITH AN INTELLIGENT INFORMATION SHARING AMONG INDIVIDUALS

    Tapabrata Ray;Pankaj Saini

  • Differential Evolution With Dynamic Parameters Selection for Optimization Problems

    Ruhul A. Sarker;Saber M. Elsayed;Tapabrata Ray

  • A Pareto Corner Search Evolutionary Algorithm and Dimensionality Reduction in Many-Objective Optimization Problems

    H. K. Singh;A. Isaacs;T. Ray

  • MULTIOBJECTIVE DESIGN OPTIMIZATION BY AN EVOLUTIONARY ALGORITHM

    Tapabrata Ray;Kang Tai;Kin Chye Seow

  • Infeasibility Driven Evolutionary Algorithm for Constrained Optimization

    Tapabrata Ray;Hemant Kumar Singh;Amitay Isaacs;Warren Smith

  • A SOCIO-BEHAVIOURAL SIMULATION MODEL FOR ENGINEERING DESIGN OPTIMIZATION

    Shamim Akhtar;Kang Tai;Tapabrata Ray

  • An improved evolutionary algorithm for solving multi-objective crop planning models

    Ruhul Sarker;Tapabrata Ray

  • Evolutionary Algorithms for Dynamic Economic Dispatch Problems

    M. F. Zaman;Saber M. Elsayed;Tapabrata Ray;Ruhul A. Sarker

  • A Multiple Surrogate Assisted Decomposition-Based Evolutionary Algorithm for Expensive Multi/Many-Objective Optimization

    Ahsanul Habib;Hemant Kumar Singh;Tinkle Chugh;Tapabrata Ray

  • An evolutionary algorithm for constrained optimization

    Tapabrata Ray;Tai Kang;Seow Kian Chye

  • A cooperative coevolutionary algorithm with Correlation based Adaptive Variable Partitioning

    Tapabrata Ray;Xin Yao

  • Vibration-based inverse algorithms for detection of delamination in composites

    Zhifang Zhang;Krishna Shankar;Tapabrata Ray;Evgeny V. Morozov

  • Constrained robust optimal design using a multiobjective evolutionary algorithm

    T. Ray

  • Design Synthesis of Path Generating Compliant Mechanisms by Evolutionary Optimization of Topology and Shape

    Kang Tai;Guang Yu Cui;Tapabrata Ray

  • An Enhanced Decomposition-Based Evolutionary Algorithm With Adaptive Reference Vectors

    Md. Asafuddoula;Hemant Kumar Singh;Tapabrata Ray

  • A swarm with an effective information sharing mechanism for unconstrained and constrained single objective optimisation problems

    T. Ray;K.M. Liew

  • An adaptive constraint handling approach embedded MOEA/D

    Asafuddoula;Tapabrata Ray;Ruhul Sarker;Khairul Alam

Frequent Co-Authors

Ruhul A. Sarker
Ruhul A. Sarker University of New South Wales
Saber M. Elsayed
Saber M. Elsayed University of New South Wales
K.M. Liew
K.M. Liew City University of Hong Kong
Kang Tai
Kang Tai Nanyang Technological University
Michael J. Ryan
Michael J. Ryan University of New South Wales
Xin Yao
Xin Yao Lingnan University
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Sami Kara
Sami Kara University of New South Wales
Ming Jen Tan
Ming Jen Tan Nanyang Technological University

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