World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
10846
World Ranking
6752
National Ranking
2977

Carlos Scheidegger 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 Carlos Scheidegger 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: 120 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Carlos Scheidegger 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 Carlos Scheidegger 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Carlos Scheidegger is affiliated with the University of Arizona in the United States. Their research primarily spans the field of Computer Science, with specializations across several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing, and Statistical and Nonlinear Physics.

The scientist's work addresses a range of topics, notably Data Visualization and Analytics, Anomaly Detection Techniques and Applications, Explainable Artificial Intelligence (XAI), Bayesian Modeling and Causal Inference, Machine Learning and Data Classification, Data Management and Algorithms, as well as Software System Performance and Reliability.

Carlos Scheidegger has contributed to a variety of scholarly publication venues. Frequent outlets for their work include arXiv (Cornell University), IEEE Transactions on Visualization and Computer Graphics, Communications of the ACM, The Astronomical Journal, and Distill.

Some of their recent papers are:

  • "The (Im)possibility of fairness," 2021, Communications of the ACM
  • "Problems with Shapley-value-based explanations as feature importance measures," 2020, arXiv (Cornell University)
  • "The ANTARES Astronomical Time-domain Event Broker," 2021, The Astronomical Journal
  • "Human-in-the-loop Extraction of Interpretable Concepts in Deep Learning Models," 2021, IEEE Transactions on Visualization and Computer Graphics

Carlos Scheidegger frequently collaborates with other researchers. Notable coauthors include Zhenge Zhao, Sorelle A. Friedler, Suresh Venkatasubramanian, Mingwei Li, and Joshua A. Levine.

Best Publications

  • Certifying and Removing Disparate Impact

    Michael Feldman;Sorelle A. Friedler;John Moeller;Carlos Scheidegger

  • VisTrails: visualization meets data management

    Steven P. Callahan;Juliana Freire;Emanuele Santos;Carlos E. Scheidegger

  • A comparative study of fairness-enhancing interventions in machine learning

    Sorelle A. Friedler;Carlos Scheidegger;Suresh Venkatasubramanian;Sonam Choudhary

  • VisTrails: enabling interactive multiple-view visualizations

    L. Bavoil;S.P. Callahan;P.J. Crossno;J. Freire

  • On the (im)possibility of fairness

    Sorelle A. Friedler;Carlos Scheidegger;Suresh Venkatasubramanian

  • Managing rapidly-evolving scientific workflows

    Juliana Freire;Cláudio T. Silva;Steven P. Callahan;Emanuele Santos

  • Auditing black-box models for indirect influence

    Philip Adler;Casey Falk;Sorelle A. Friedler;Tionney Nix

  • Nanocubes for Real-Time Exploration of Spatiotemporal Datasets

    Lauro Lins;James T. Klosowski;Carlos Scheidegger

  • Special Issue: The First Provenance Challenge

    Luc Moreau;Bertram Ludäscher;Ilkay Altintas;Roger S. Barga

  • The First Provenance Challenge

    Luc Moreau;Bertram Ludaescher;Ilkay Altintas;Roger S. Barga

  • Runaway Feedback Loops in Predictive Policing

    Danielle Ensign;Sorelle A. Friedler;Scott Neville;Carlos Eduardo Scheidegger

  • Multilevel agglomerative edge bundling for visualizing large graphs

    Emden R. Gansner;Yifan Hu;Stephen North;Carlos Scheidegger

  • The (Im)possibility of fairness: different value systems require different mechanisms for fair decision making

    Sorelle A. Friedler;Carlos Scheidegger;Suresh Venkatasubramanian

  • SynMap2 and SynMap3D: web-based whole-genome synteny browsers

    Asher Haug-Baltzell;Sean A. Stephens;Sean Davey;Carlos Eduardo Scheidegger

  • Managing the Evolution of Dataflows with VisTrails

    S.P. Callahan;J. Freire;E. Santos;C.E. Scheidegger

  • Tackling the Provenance Challenge one layer at a time

    Carlos Scheidegger;David Koop;Emanuele Santos;Huy Vo

  • Querying and Creating Visualizations by Analogy

    C.E. Scheidegger;H.T. Vo;D. Koop;J. Freire

  • Querying and re-using workflows with VsTrails

    Carlos E. Scheidegger;Huy T. Vo;David Koop;Juliana Freire

  • Problems with Shapley-value-based explanations as feature importance measures

    I. Elizabeth Kumar;Suresh Venkatasubramanian;Carlos Scheidegger;Sorelle Friedler

  • Machine Learning-based Brokers for Real-time Classification of the LSST Alert Stream

    Gautham Narayan;Tayeb Zaidi;Monika D. Soraisam;Zhe Wang

  • An Algebraic Process for Visualization Design

    Gordon L. Kindlmann;Carlos Eduardo Scheidegger

Frequent Co-Authors

Cláudio T. Silva
Cláudio T. Silva New York University
Juliana Freire
Juliana Freire New York University
Thomas Matheson
Thomas Matheson National Optical-Infrared Astronomy Research Lab
Richard T. Snodgrass
Richard T. Snodgrass University of Arizona
Remco Chang
Remco Chang Tufts University
Stephen G. Kobourov
Stephen G. Kobourov University of Arizona
Gordon Kindlmann
Gordon Kindlmann University of Chicago
Robert M. Kirby
Robert M. Kirby University of Utah
Edward W. Olszewski
Edward W. Olszewski University of Arizona

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