World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
13252
World Ranking
4524
National Ranking
2120

Robert J. Marks 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 J. Marks 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: 342 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Robert J. Marks 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 J. Marks 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: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Overview

Robert J. Marks is affiliated with Baylor University in the United States. Their research spans multiple fields and subfields within engineering and computer science, focusing primarily on electrical and electronic engineering, aerospace engineering, artificial intelligence, computer vision and pattern recognition, and radiology, nuclear medicine and imaging.

The primary areas of study include:

  • Radio Frequency Integrated Circuit Design
  • Energy Harvesting in Wireless Networks
  • Radar Systems and Signal Processing
  • Antenna Design and Optimization
  • Advanced SAR Imaging Techniques
  • Full-Duplex Wireless Communications
  • Advanced Power Amplifier Design

Recent publications demonstrate a diverse range of topics and collaboration with other researchers. Key papers include:

  • "Radiomics Feature Activation Maps as a New Tool for Signature Interpretability," 2020, Frontiers in Oncology
  • "Extrapolation of Load-Pull Data: A Novel Use of GAN Artificial Intelligence Image Completion," 2022, IEEE Transactions on Microwave Theory and Techniques
  • "Spurious Beam Suppression in Dual-Beam Phased Array Transmission by Impedance Tuning," 2022, IEEE Transactions on Aerospace and Electronic Systems
  • "A Plasma-Switch Impedance Tuner With Microsecond Reconfiguration," 2022, IEEE Transactions on Microwave Theory and Techniques
  • "A Low-Loss Reconfigurable Plasma Impedance Tuner for Real-Time, Frequency-Agile, High-Power RF Applications," 2022, 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022

The coauthors who have frequently collaborated with Robert J. Marks include:

  • Charles Baylis
  • Austin Egbert
  • Adam Goad
  • Trevor Van Hoosier
  • Anthony F. Martone

Published work is often found in a range of venues, reflecting the broad scope of Robert J. Marks's research interests. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Microwave Theory and Techniques
  • IEEE Transactions on Aerospace and Electronic Systems
  • 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022
  • 2022 IEEE Radar Conference (RadarConf22)

This profile presents an overview of Robert J. Marks's research contributions across engineering and computer science, highlighting engagement with topics related to radio frequency technologies, signal processing, and artificial intelligence within technical and scientific publication platforms.

Best Publications

  • Electric load forecasting using an artificial neural network

    D.C. Park;M.A. El-Sharkawi;R.J. Marks;L.E. Atlas

  • Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks

    Russell D. Reed;Robert J. Marks

  • The use of cone-shaped kernels for generalized time-frequency representations of nonstationary signals

    Y. Zhao;L.E. Atlas;R.J. Marks

  • Introduction to Shannon Sampling and Interpolation Theory

    II Robert J. Marks

  • Support vector machines for transient stability analysis of large-scale power systems

    L.S. Moulin;A.P.A. da Silva;M.A. El-Sharkawi;R.J. Marks

  • Computational Intelligence: Imitating Life

    Robert J. Marks;Jacek M. Zurada;Charles J. Robinson

  • Advanced topics in Shannon sampling and interpolation theory

    Robert J. Marks

  • Swarm intelligence for routing in communication networks

    I. Kassabalidis;M.A. El-Sharkawi;R.J. Marks;P. Arabshahi

  • Query-based learning applied to partially trained multilayer perceptrons

    J.-N. Hwang;J.J. Choi;S. Oh;R.J. Marks

  • A performance comparison of trained multilayer perceptrons and trained classification trees

    L. Atlas;J. Connor;D. Park;M. El-Sharkawi

  • Minimum power broadcast trees for wireless networks: integer programming formulations

    A. K. Das;R. J. Marks;M. El-Sharkawi;P. Arabshahi

  • An adaptively trained neural network

    D.C. Park;M.A. El-Sharkawi;R.J. Marks

  • Handbook of Fourier Analysis & Its Applications

    Robert J Marks

  • Inversion of snow parameters from passive microwave remote sensing measurements by a neural network trained with a multiple scattering model

    L. Tsang;Z. Chen;S. Oh;R.J. Marks

  • Dynamic security border identification using enhanced particle swarm optimization

    I.N. Kassabalidis;M.A. El-Sharkawi;R.J. Marks;L.S. Moulin

  • A performance comparison of trained multilayer perceptrons and trained classification trees

    L. Atlas;R. Cole;Y. Muthusamy;A. Lippman

  • Similarities of error regularization, sigmoid gain scaling, target smoothing, and training with jitter

    R. Reed;R.J. Marks;S. Oh

  • Preliminary results on using artificial neural networks for security assessment (of power systems)

    M. Aggoune;M.A. El-Sharkawi;D.C. Park;M.J. Dambourg

  • Inversion of feedforward neural networks: algorithms and applications

    C.A. Jensen;R.D. Reed;R.J. Marks;M.A. El-Sharkawi

  • Differintegral interpolation from a bandlimited signal's samples

    R. Marks;M. Hall

Frequent Co-Authors

Mohamed A. El-Sharkawi
Mohamed A. El-Sharkawi University of Washington
Les Atlas
Les Atlas University of Washington
Leung Tsang
Leung Tsang University of Michigan–Ann Arbor
Donald C. Wunsch
Donald C. Wunsch Missouri University of Science and Technology
Dimitrios Peroulis
Dimitrios Peroulis Purdue University West Lafayette
Joan E. Sanders
Joan E. Sanders University of Washington
Jenq-Neng Hwang
Jenq-Neng Hwang University of Washington
Alfred T. C. Chang
Alfred T. C. Chang Goddard Space Flight Center
Shannon D. Blunt
Shannon D. Blunt University of Kansas
Michael C. Wicks
Michael C. Wicks University of Dayton

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