World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
10970
World Ranking
11893
National Ranking
152

Chang Wook Ahn 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 Chang Wook Ahn 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: 225 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Chang Wook Ahn 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 Chang Wook Ahn 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Chang Wook Ahn is affiliated with the Gwangju Institute of Science and Technology in South Korea and has contributed extensively to the field of computer science, authoring 95 publications. Their research primarily focuses on artificial intelligence, computer vision and pattern recognition, signal processing, sociology and political science, and electrical and electronic engineering.

The scientist's work includes a variety of topics within these fields, notably:

  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Artificial Intelligence in Games
  • Reinforcement Learning in Robotics
  • Quantum Computing Algorithms and Architecture
  • Digital Games and Media
  • Speech and Audio Processing

Ahn has published frequently in well-known venues, with multiple contributions to:

  • IEEE Access
  • Electronics
  • Mathematics
  • Expert Systems with Applications
  • International Journal of Bio-Inspired Computation

Selected recent papers include:

  • "A Novel YOLOv3 Algorithm-Based Deep Learning Approach for Waste Segregation: Towards Smart Waste Management" (2020) in Electronics
  • "A fast and efficient image watermarking scheme based on Deep Neural Network" (2021) in Pattern Recognition Letters
  • "Regression tree ensemble learning-based prediction of the heating and cooling loads of residential buildings" (2022) in Building Simulation
  • "Blind Image Watermarking for Localization and Restoration of Color Images" (2020) in IEEE Access
  • "Data Analytics and Mathematical Modeling for Simulating the Dynamics of COVID-19 Epidemic-A Case Study of India" (2021) in Electronics

The scientist has collaborated repeatedly with several coauthors most frequently including:

  • Man-Je Kim (14 publications)
  • Jun Suk Kim (7 publications)
  • Nikhil Pachauri (6 publications)
  • Sanghoun Oh (5 publications)
  • Om Prakash Verma (4 publications)

This profile reflects a broad and active engagement in computer science research with a focus on developing and applying artificial intelligence algorithms, optimization methods, and image processing techniques. The collaboration network and publication history indicate work spanning multiple related subfields and topics, contributing to ongoing developments in these areas.

Best Publications

  • Spatial Modulation

    R.Y. Mesleh;H. Haas;S. Sinanovic;Chang Wook Ahn

  • Spatial Modulation

    Unknown

  • A genetic algorithm for shortest path routing problem and the sizing of populations

    Chang Wook Ahn;R.S. Ramakrishna

  • Spatial Modulation - A New Low Complexity Spectral Efficiency Enhancing Technique

    R. Mesleh;H. Haas;Chang Wook Ahn;Sangboh Yun

  • Elitism-based compact genetic algorithms

    Chang Wook Ahn;R.S. Ramakrishna

  • A robust image watermarking technique using SVD and differential evolution in DCT domain

    Musrrat Ali;Chang Wook Ahn;Millie Pant

  • Advances in Evolutionary Algorithms

    Chang Wook Ahn

  • An optimized watermarking technique based on self-adaptive DE in DWT-SVD transform domain

    Musrrat Ali;Chang Wook Ahn

  • Asilomar Conference on Signals, Systems, and Computers

    S. Ganesan;R. Mesleh;Harald Haas;C. W. Ahn

  • An image watermarking scheme in wavelet domain with optimized compensation of singular value decomposition via artificial bee colony

    Musrrat Ali;Chang Wook Ahn;Millie Pant;Patrick Siarry

  • A Novel YOLOv3 Algorithm-Based Deep Learning Approach for Waste Segregation: Towards Smart Waste Management

    Saurav Kumar;Drishti Yadav;Himanshu Gupta;Om Prakash Verma

  • Robust and false positive free watermarking in IWT domain using SVD and ABC

    Irshad Ahmad Ansari;Millie Pant;Chang Wook Ahn

  • Evolutionary Approaches To Minimizing Network Coding Resources

    Minkyu Kim;M. Medard;V. Aggarwal;U.-M. O'Reilly

  • Shortest path routing algorithm using Hopfield neural network

    C.W. Ahn;R.S. Ramakrishna;C.G. Kang;I.C. Choi

  • SVD based fragile watermarking scheme for tamper localization and self-recovery

    Irshad Ahmad Ansari;Millie Pant;Chang Wook Ahn

  • On the Performance of Spatial Modulation OFDM

    S. Ganesan;R. Mesleh;H. Haas;Chang Wook Ahn

  • Differential evolution algorithm for the selection of optimal scaling factors in image watermarking

    Musrrat Ali;Chang Wook Ahn;Patrick Siarry

  • Real-Coded Bayesian Optimization Algorithm: Bringing the Strength of BOA into the Continuous World

    Chang Wook Ahn;Rudrapatna S. Ramakrishna;David E. Goldberg

  • QoS provisioning dynamic connection-admission control for multimedia wireless networks using a Hopfield neural network

    Chang Wook Ahn;R.S. Ramakrishna

  • Advances in Evolutionary Algorithms: Theory, Design and Practice

    Unknown

  • Multi-level image thresholding by synergetic differential evolution

    Musrrat Ali;Chang Wook Ahn;Millie Pant

  • On the practical genetic algorithms

    Chang Wook Ahn;Sanghoun Oh;R. S. Ramakrishna

Frequent Co-Authors

Millie Pant
Millie Pant Indian Institute of Technology Roorkee
Raed Mesleh
Raed Mesleh German Jordanian University
Harald Haas
Harald Haas University of Cambridge
David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Patrick Siarry
Patrick Siarry Paris-Est Créteil University
Moongu Jeon
Moongu Jeon Gwangju Institute of Science and Technology
Sanghoon Lee
Sanghoon Lee Yonsei University
Michelle Effros
Michelle Effros California Institute of Technology

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