World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8721
World Ranking
6509
National Ranking
258

Mark Coates 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 Mark Coates 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: 209 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Mark Coates 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 Mark Coates 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Mark Coates is affiliated with McGill University in Canada and has produced a substantial body of research primarily within the field of Computer Science. Their work encompasses a diverse range of subfields including Artificial Intelligence, Information Systems, Signal Processing, Computer Vision and Pattern Recognition, and Statistics and Probability.

Their contributions cover multiple main topics and areas of research interest such as:

  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques
  • Time Series Analysis and Forecasting
  • Topic Modeling
  • Machine Learning and Algorithms
  • Complex Network Analysis Techniques
  • Traffic Prediction and Management Techniques

Mark Coates has published extensively with a notable concentration in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology
  • 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)
  • IEEE Transactions on Visualization and Computer Graphics

Frequent collaborators include:

  • Yingxue Zhang
  • Soumyasundar Pal
  • Florence Regol
  • Antonios Valkanas
  • Chen Ma

Representative recent papers by Mark Coates include:

  • Memory Augmented Graph Neural Networks for Sequential Recommendation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Microwave Breast Screening Prototype: System Miniaturization With IC Pulse Radio, 2020, IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology
  • Knowledge-Enhanced Top-K Recommendation in Poincaré Ball, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction, 2021, 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD)

Best Publications

  • Network Tomography: Recent Developments

    Rui Castro;Mark Coates;Gang Liang;Robert Nowak

  • Distributed particle filters for sensor networks

    Mark Coates

  • Distributed Average Consensus With Dithered Quantization

    T.C. Aysal;M.J. Coates;M.G. Rabbat

  • Maximum likelihood network topology identification from edge-based unicast measurements

    Mark Coates;Rui Castro;Robert Nowak;Manik Gadhiok

  • Multifractal Cross-Traffic Estimation

    Vinay Joseph Ribeiro;Mark J. Coates;Rudolf H. Riedi;Shriram Sarvotham

  • Network Loss Inference Using Unicast End-to-End Measurement

    Mark J. Coates;Robert David Nowak

  • Network delay tomography

    Yolanda Tsang;M. Coates;R.D. Nowak

  • Memory Augmented Graph Neural Networks for Sequential Recommendation

    Chen Ma;Liheng Ma;Yingxue Zhang;Jianing Sun

  • An Early Clinical Study of Time-Domain Microwave Radar for Breast Health Monitoring

    Emily Porter;Mark Coates;Milica Popovic

  • Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares

    T. Ahmed;M. Coates;A. Lakhina

  • Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification

    Yingxue Zhang;Soumyasundar Pal;Mark Coates;Deniz Ustebay

  • Machine learning approaches to network anomaly detection

    Tarem Ahmed;Boris Oreshkin;Mark Coates

  • Neighbor Interaction Aware Graph Convolution Networks for Recommendation

    Jianing Sun;Yingxue Zhang;Wei Guo;Huifeng Guo

  • Time-Domain Multistatic Radar System for Microwave Breast Screening

    E. Porter;E. Kirshin;A. Santorelli;M. Coates

  • Radio-Frequency Tomography for Passive Indoor Multitarget Tracking

    Santosh Nannuru;Yunpeng Li;Yan Zeng;Mark Coates

  • Multiple source, multiple destination network tomography

    M. Rabbat;R. Nowak;M. Coates

  • Likelihood based hierarchical clustering

    R.M. Castro;M.J. Coates;R.D. Nowak

  • Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements

    Xi Chen;Andrea Edelstein;Yunpeng Li;Mark Coates

  • Distributed Average Consensus using Probabilistic Quantization

    Tuncer C. Aysal;Mark Coates;Michael Rabbat

  • Optimization and Analysis of Distributed Averaging With Short Node Memory

    Boris N Oreshkin;Mark J Coates;Michael G Rabbat

  • Epidemiological Modelling of Peer-to-Peer Viruses and Pollution

    R. Thommes;M. Coates

Frequent Co-Authors

Michael Rabbat
Michael Rabbat Facebook (United States)
Robert Nowak
Robert Nowak University of Wisconsin–Madison
Xue Liu
Xue Liu McGill University
Xiuqiang He
Xiuqiang He Huawei Technologies (China)
Richard G. Baraniuk
Richard G. Baraniuk Rice University
Peter Henderson
Peter Henderson University of Oxford
Arnaud Doucet
Arnaud Doucet University of Oxford
Anna Scaglione
Anna Scaglione Cornell University
Henry Leung
Henry Leung University of Calgary
Michael Gastpar
Michael Gastpar École Polytechnique Fédérale de Lausanne

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