World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
83
Citations
105549
World Ranking
872
National Ranking
475

Carlos Guestrin 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 Guestrin 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: 196 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Carlos Guestrin 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 Guestrin 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: 83 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2006 - Fellow of Alfred P. Sloan Foundation

Overview

Carlos Guestrin is affiliated with Stanford University in the United States. Their main field of study is Computer Science, with a specialized focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Endocrinology, Diabetes and Metabolism, Software, and Sociology and Political Science.

Their research covers a variety of topics. Notable among these are:

  • Topic Modeling
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques
  • Diabetes Management and Research
  • Advanced Neural Network Applications
  • Explainable Artificial Intelligence (XAI)
  • Diabetes and associated disorders

Frequent co-authors include:

  • Tatsunori Hashimoto
  • Matei Zaharia
  • Emily B. Fox
  • David Scheinker
  • David M. Maahs

Carlos Guestrin has published predominantly in the venue arXiv (Cornell University), contributing 23 publications. Other publication venues include Proceedings of the ACM on Management of Data, Nature, bioRxiv (Cold Spring Harbor Laboratory), and JAMA Network Open.

Some of their recent papers include:

  • "AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback," 2023, arXiv (Cornell University)
  • "Mobility trends provide a leading indicator of changes in SARS-CoV-2 transmission," 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • "Disparities in Hemoglobin A1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring," 2023, JAMA Network Open
  • "ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data," 2024, Proceedings of the ACM on Management of Data
  • "Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks," 2023, arXiv (Cornell University)

The scientist has been recognized as a Fellow of the Alfred P. Sloan Foundation in 2006.

Best Publications

  • XGBoost: A Scalable Tree Boosting System

    Tianqi Chen;Carlos Guestrin

  • “Why Should I Trust You?”: Explaining the Predictions of Any Classifier

    Marco Túlio Ribeiro;Sameer Singh;Carlos Guestrin

  • Cost-effective outbreak detection in networks

    Jure Leskovec;Andreas Krause;Carlos Guestrin;Christos Faloutsos

  • PowerGraph: distributed graph-parallel computation on natural graphs

    Joseph E. Gonzalez;Yucheng Low;Haijie Gu;Danny Bickson

  • Anchors: High-Precision Model-Agnostic Explanations

    Marco Tulio Ribeiro;Sameer Singh;Carlos Guestrin

  • Max-Margin Markov Networks

    Ben Taskar;Carlos Guestrin;Daphne Koller

  • Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies

    Andreas Krause;Ajit Singh;Carlos Guestrin

  • Distributed GraphLab: a framework for machine learning and data mining in the cloud

    Yucheng Low;Danny Bickson;Joseph Gonzalez;Carlos Guestrin

  • Model-driven data acquisition in sensor networks

    Amol Deshpande;Carlos Guestrin;Samuel R. Madden;Joseph M. Hellerstein

  • GraphChi: large-scale graph computation on just a PC

    Aapo Kyrola;Guy Blelloch;Carlos Guestrin

  • TVM: an automated end-to-end optimizing compiler for deep learning

    Tianqi Chen;Thierry Moreau;Ziheng Jiang;Lianmin Zheng

  • Beyond accuracy: Behavioral testing of NLP models with checklist

    Marco Tulio Ribeiro;Tongshuang Wu;Carlos Guestrin;Sameer Singh

  • Model-Agnostic Interpretability of Machine Learning.

    Marco Túlio Ribeiro;Sameer Singh;Carlos Guestrin

  • Training Deep Nets with Sublinear Memory Cost.

    Tianqi Chen;Bing Xu;Chiyuan Zhang;Carlos Guestrin

  • Learning structured prediction models: a large margin approach

    Ben Taskar;Vassil Chatalbashev;Daphne Koller;Carlos Guestrin

  • The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms

    Avi Ostfeld;James G. Uber;Elad Salomons;Jonathan W. Berry

  • GraphLab: a new framework for parallel machine learning

    Yucheng Low;Joseph Gonzalez;Aapo Kyrola;Danny Bickson

  • Stochastic Gradient Hamiltonian Monte Carlo

    Tianqi Chen;Emily Fox;Carlos Guestrin

  • Efficient solution algorithms for factored MDPs

    Carlos Guestrin;Daphne Koller;Ronald Parr;Shobha Venkataraman

  • Distributed regression: an efficient framework for modeling sensor network data

    Carlos Guestrin;Peter Bodik;Romain Thibaux;Mark Paskin

Frequent Co-Authors

Andreas Krause
Andreas Krause ETH Zurich
Sameer Singh
Sameer Singh University of California, Irvine
Joseph E. Gonzalez
Joseph E. Gonzalez University of California, Berkeley
Joseph M. Hellerstein
Joseph M. Hellerstein University of California, Berkeley
Daphne Koller
Daphne Koller insitro Inc.
Jure Leskovec
Jure Leskovec Stanford University
Luis Ceze
Luis Ceze University of Washington
Arvind Krishnamurthy
Arvind Krishnamurthy University of Washington
Amol Deshpande
Amol Deshpande University of Maryland, College Park
Eric Horvitz
Eric Horvitz Microsoft (United States)

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