World's Best Scientists 2026 revealed!
Robert C. Williamson

Robert C. Williamson

D-Index & Metrics

Computer Science

D-Index
54
Citations
25992
World Ranking
4432
National Ranking
195

Robert C. Williamson 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 C. Williamson 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: 189 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Robert C. Williamson 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 C. Williamson 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 C. Williamson is affiliated with the University of Tübingen in Germany. Their research primarily centers on computer science, with a focus on several subfields including artificial intelligence, management science and operations research, statistics and probability, computational theory and mathematics, and safety research.

The scientist's work covers a range of topics. Notable areas of study include Bayesian modeling and causal inference, explainable artificial intelligence (XAI), risk and portfolio optimization, rough sets and fuzzy logic, ethics and social impacts of AI, statistical methods and inference, and the philosophy and history of science.

Robert C. Williamson has contributed to various publication venues. The most frequent venue is arXiv (Cornell University), with 22 publications. Other venues include Harvard Data Science Review, Chemometrics and Intelligent Laboratory Systems, Computer, and White Rose Research Online (University of Leeds, The University of Sheffield, University of York).

Frequent coauthors in their research include Rabanus Derr, Christian Fröhlich, Benedikt Höltgen, and Zac Cranko.

Recent papers authored or coauthored by Robert C. Williamson and colleagues include:

  • Classification of cow diet based on milk Mid Infrared Spectra: A data analysis competition at the "International Workshop on Spectroscopy and Chemometrics 2022" (2023), Chemometrics and Intelligent Laboratory Systems
  • PAC-Bayesian Bound for the Conditional Value at Risk (2020), arXiv (Cornell University)
  • Assessing AI Fairness in Finance (2022), Computer
  • Information Processing Equalities and the Information-Risk Bridge (2022), arXiv (Cornell University)
  • Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity (2022), arXiv (Cornell University)

Best Publications

  • Estimating the Support of a High-Dimensional Distribution

    Bernhard Schölkopf;John C. Platt;John C. Shawe-Taylor;Alex J. Smola

  • New Support Vector Algorithms

    Bernhard Schölkopf;Alex J. Smola;Robert C. Williamson;Peter L. Bartlett

  • Online learning with kernels

    J. Kivinen;A.J. Smola;R.C. Williamson

  • Support Vector Method for Novelty Detection

    Bernhard Schölkopf;Robert C Williamson;Alex J. Smola;John Shawe-Taylor

  • Structural risk minimization over data-dependent hierarchies

    J. Shawe-Taylor;P.L. Bartlett;R.C. Williamson;M. Anthony

  • Learning the Kernel with Hyperkernels

    Cheng Soon Ong;Alexander J. Smola;Robert C. Williamson

  • Particle filtering algorithms for tracking an acoustic source in a reverberant environment

    D.B. Ward;E.A. Lehmann;R.C. Williamson

  • Theory and design of broadband sensor arrays with frequency invariant far‐field beam patterns

    Darren B. Ward;Rodney A. Kennedy;Robert C. Williamson

  • Shrinking the Tube: A New Support Vector Regression Algorithm

    Bernhard Schölkopf;Peter L. Bartlett;Alex J. Smola;Robert C Williamson

  • The Need for Open Source Software in Machine Learning

    Sören Sonnenburg;Mikio L. Braun;Cheng Soon Ong;Samy Bengio

  • The cost of fairness in binary classification

    Aditya Krishna Menon;Robert C Williamson

  • A PAC analysis of a Bayesian estimator

    John Shawe-Taylor;Robert C. Williamson

  • Learning with symmetric label noise: the importance of being unhinged

    Brendan van Rooyen;Aditya Krishna Menon;Robert C. Williamson

  • Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators

    R.C. Williamson;A.J. Smola;B. Scholkopf

  • Efficient agnostic learning of neural networks with bounded fan-in

    Wee Sun Lee;P.L. Bartlett;R.C. Williamson

  • Support vector regression with automatic accuracy control.

    B Schölkopf;P Bartlett;AJ Smola;R Williamson

  • Fat-shattering and the learnability of real-valued functions

    Peter L. Bartlett;Philip M. Long;Robert C. Williamson

  • Clustering: Science or Art?

    U von Luxburg;R Williamson;I Guyon

  • Composite Binary Losses

    Mark D. Reid;Robert C. Williamson

  • Information, Divergence and Risk for Binary Experiments

    Mark D. Reid;Robert C. Williamson

  • Clustering: science or art?

    Ulrike Von Luxburg;Robert C. Williamson;Isabelle Guyon

Frequent Co-Authors

Alexander J. Smola
Alexander J. Smola Amazon (United States)
Peter L. Bartlett
Peter L. Bartlett University of California, Berkeley
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Rodney A. Kennedy
Rodney A. Kennedy Australian National University
John Shawe-Taylor
John Shawe-Taylor University College London
Aditya Krishna Menon
Aditya Krishna Menon Google (United States)
Richard Nock
Richard Nock Australian National University
Wee Sun Lee
Wee Sun Lee National University of Singapore
Thushara D. Abhayapala
Thushara D. Abhayapala Australian National University
Iven Mareels
Iven Mareels IBM (United States)

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