World's Best Scientists 2026 revealed!
William G. Macready

William G. Macready

D-Index & Metrics

Computer Science

D-Index
36
Citations
22860
World Ranking
10952
National Ranking
435

William G. Macready 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 William G. Macready 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: 83 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

William G. Macready 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 William G. Macready 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

William G. Macready is affiliated with D-Wave Systems in Canada, where their research primarily focuses on computational and engineering challenges related to quantum computing and robotics.

Their recent publications cover a range of topics and venues, including:

  • Solving SAT (and MaxSAT) with a quantum annealer: Foundations, encodings, and preliminary results, 2020, Information and Computation
  • Neural-Guided Runtime Prediction of Planners for Improved Motion and Task Planning with Graph Neural Networks, 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • Neural-Guided RuntimePrediction of Planners for Improved Motion and Task Planning with Graph Neural Networks, 2022, arXiv (Cornell University)

The scientist frequently collaborates with other researchers, including:

  • Simon Odense (2 publications)
  • Zhengbing Bian (1 publication)
  • Fabián A. Chudak (1 publication)
  • Aidan Roy (1 publication)
  • Roberto Sebastiani (1 publication)

Research venues where their work appears regularly are:

  • Information and Computation
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • arXiv (Cornell University)

William G. Macready's fields of study are rooted mainly in computer science and engineering, with specific attention to the following subfields:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Control and Systems Engineering
  • Information Systems

Their research spans multiple main topics including:

  • Robotic Path Planning Algorithms
  • Robot Manipulation and Learning
  • Multimodal Machine Learning Applications
  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Cloud Computing and Resource Management

This profile highlights Macready's involvement in advancing methods for motion and task planning through neural-guided runtime prediction, as well as foundational work on quantum annealing applied to satisfiability problems. The integration of machine learning techniques with robotics and quantum computing underlines the interdisciplinary nature of their research portfolio.

Best Publications

  • No free lunch theorems for optimization

    D.H. Wolpert;W.G. Macready

  • No Free Lunch Theorems for Search

    David H. Wolpert;William G. Macready

  • Optimal search on a technology landscape

    Stuart Kauffman;José Lobo;William G. Macready

  • A practical heuristic for finding graph minors

    Jun Cai;William G. Macready;Aidan Roy

  • Coevolutionary free lunches

    D.H. Wolpert;W.G. Macready

  • A Robust Learning Approach to Domain Adaptive Object Detection

    Mehran Khodabandeh;Arash Vahdat;Mani Ranjbar;William Macready

  • An Efficient Method To Estimate Bagging‘s Generalization Error

    David H. Wolpert;William G. Macready

  • Bandit problems and the exploration/exploitation tradeoff

    W.G. Macready;D.H. Wolpert

  • Discrete optimization using quantum annealing on sparse Ising models

    Zhengbing Bian;Fabian Chudak;Robert Israel;Brad Lackey

  • Experimental determination of Ramsey numbers.

    Zhengbing Bian;Fabian Chudak;William G. Macready;Lane Clark

  • Image recognition with an adiabatic quantum computer I. Mapping to quadratic unconstrained binary optimization

    Hartmut Neven;Geordie Rose;William G. Macready

  • CATARACTS: Challenge on automatic tool annotation for cataRACT surgery

    Hassan Al Hajj;Mathieu Lamard;Pierre-Henri Conze;Soumali Roychowdhury

  • Mapping Constrained Optimization Problems to Quantum Annealing with Application to Fault Diagnosis

    Zhengbing Bian;Fabian Chudak;Robert Brian Israel;Brad Lackey

  • Adaptive and reliable system and method for operations management

    Isaac Saias;Vince Darley;Stuart Kauffman;Fred Federspiel

  • Training a Binary Classifier with the Quantum Adiabatic Algorithm

    Hartmut Neven;Vasil S. Denchev;Geordie Rose;William G. Macready

  • Semi-Supervised Semantic Image Segmentation With Self-Correcting Networks

    Mostafa S. Ibrahim;Arash Vahdat;Mani Ranjbar;William G. Macready

  • Graph embedding techniques

    Michael Coury;William G. Macready;David Grant

  • Processing relational database problems using analog processors

    William G. Macready;Michael D. Coury;Ivan King Yu Sham

  • Parameter space exploration with Gaussian process trees

    Robert B. Gramacy;Herbert K. H. Lee;William G. Macready

  • What Makes an Optimization Problem Hard

    William G. Macready;David H. Wolpert

  • Training a Large Scale Classifier with the Quantum Adiabatic Algorithm

    Hartmut Neven;Vasil S. Denchev;Geordie Rose;William G. Macready

Frequent Co-Authors

David H. Wolpert
David H. Wolpert Santa Fe Institute
Stuart A. Kauffman
Stuart A. Kauffman University of Vermont
Hartmut Neven
Hartmut Neven Google (United States)
Alán Aspuru-Guzik
Alán Aspuru-Guzik University of Toronto
Roberto Sebastiani
Roberto Sebastiani University of Trento
Danail Stoyanov
Danail Stoyanov University College London
Pheng-Ann Heng
Pheng-Ann Heng Chinese University of Hong Kong
Eleanor Rieffel
Eleanor Rieffel Ames Research Center
Robert B. Gramacy
Robert B. Gramacy Virginia Tech
Aurélio Campilho
Aurélio Campilho University of Porto

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