World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
12821
World Ranking
3448
National Ranking
99

Hussein A. Abbass 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 Hussein A. Abbass 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: 445 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Hussein A. Abbass 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 Hussein A. Abbass 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: 59 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2020 - IEEE Fellow For contributions to evolutionary learning and optimization

Overview

Hussein A. Abbass is affiliated with the University of New South Wales in Australia. Their research spans primarily the fields of Computer Science and Engineering, with a focus on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Aerospace Engineering, and Media Technology.

Their work covers several key topics including Robotic Path Planning Algorithms, Distributed Control Multi-Agent Systems, Modular Robots and Swarm Intelligence, Human-Automation Interaction and Safety, Advanced Vision and Imaging, Image Processing Techniques and Applications, and Reinforcement Learning in Robotics.

Abbass has contributed to numerous publications, frequently appearing in venues such as arXiv (Cornell University), IEEE Computational Intelligence Magazine, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Artificial Intelligence.

Recent notable papers include:

  • Towards Real-Time Monocular Depth Estimation for Robotics: A Survey, 2022, IEEE Transactions on Intelligent Transportation Systems
  • BrainPrint: EEG biometric identification based on analyzing brain connectivity graphs, 2020, Pattern Recognition
  • IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, IEEE Transactions on Emerging Topics in Computational Intelligence
  • Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments, 2020, Frontiers in Neuroscience
  • Modified continuous Ant Colony Optimisation for multiple Unmanned Ground Vehicle path planning, 2022, Expert Systems with Applications

Their frequent co-authors include Sreenatha G. Anavatti, Matthew Garratt, Carlos A. Coello Coello, Kathryn Kasmarik, and Aya Hussein.

In addition to journal articles, Hussein A. Abbass has authored books published by Springer International Publishing, such as "Shepherding UxVs for Human-Swarm Teaming" (2021).

The researcher has been recognized as an IEEE Fellow in 2020 for contributions to evolutionary learning and optimization.

Best Publications

  • PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems

    H.A. Abbass;R. Sarker;C. Newton

  • The self-adaptive Pareto differential evolution algorithm

    H.A. Abbass

  • MBO: marriage in honey bees optimization-a Haplometrosis polygynous swarming approach

    H.A. Abbass

  • An evolutionary artificial neural networks approach for breast cancer diagnosis

    Hussein A. Abbass

  • Advances in Computational Intelligence

    Jing Liu;Cesare Alippi;Bernadette Bouchon-Meunier;Garrison W. Greenwood

  • THE PARETO DIFFERENTIAL EVOLUTION ALGORITHM

    Hussein A. Abbass;Ruhul A. Sarker

  • Data Mining: A Heuristic Approach

    Hussein Abbass;Charles Newton;Ruhul Sarker

  • Speeding up backpropagation using multiobjective evolutionary algorithms

    Hussein A. Abbass

  • Hierarchical Deep Reinforcement Learning for Continuous Action Control

    Zhaoyang Yang;Kathryn Merrick;Lianwen Jin;Hussein A. Abbass

  • Multiobjective optimization for dynamic environments

    L.T. Bui;H.A. Abbass;J. Branke

  • A Memetic Pareto Evolutionary Approach to Artificial Neural Networks

    Hussein A. Abbass

  • Towards Real-Time Monocular Depth Estimation for Robotics: A Survey

    Unknown

  • Social Integration of Artificial Intelligence: Functions, Automation Allocation Logic and Human-Autonomy Trust

    Hussein A. Abbass

  • 2012 IEEE Congress on Evolutionary Computation

    Hussein Abbass;Daryl Essam;Ruhul Sarker

  • Pareto neuro-evolution: constructing ensemble of neural networks using multi-objective optimization

    H.A. Abbass

  • Multimodal Fusion for Objective Assessment of Cognitive Workload: A Review

    Essam Debie;Raul Fernandez Rojas;Justin Fidock;Michael Barlow

  • Convolutional Neural Networks Using Dynamic Functional Connectivity for EEG-Based Person Identification in Diverse Human States

    Min Wang;Heba El-Fiqi;Jiankun Hu;Hussein A. Abbass

  • Neural-Based Learning Classifier Systems

    H.H. Dam;H.A. Abbass;C. Lokan;Xin Yao

  • A Monogenous MBO Approach to Satisfiability

    Hussein A. Abbass

  • Adaptive Cross-Generation Differential Evolution Operators for Multiobjective Optimization

    Xin Qiu;Jian-Xin Xu;Kay Chen Tan;Hussein A. Abbass

  • Grammar model-based program evolution

    Y. Shan;R.I. McKay;R. Baxter;H. Abbass

  • Fitness inheritance for noisy evolutionary multi-objective optimization

    Lam T. Bui;Hussein A. Abbass;Daryl Essam

  • Classification Rule Discovery with Ant Colony Optimization.

    Bo Liu;Hussein A. Abbass;Robert I. McKay

Frequent Co-Authors

Ruhul A. Sarker
Ruhul A. Sarker University of New South Wales
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
Jing Liu
Jing Liu Xidian University
Daryl Essam
Daryl Essam University of New South Wales
Saber M. Elsayed
Saber M. Elsayed University of New South Wales
Jiankun Hu
Jiankun Hu University of New South Wales
Kalyanmoy Deb
Kalyanmoy Deb Michigan State University
David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Jürgen Branke
Jürgen Branke University of Warwick
Xiaodong Li
Xiaodong Li University of Virginia

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