World's Best Scientists 2026 revealed!
David Sontag

David Sontag

D-Index & Metrics

Computer Science

D-Index
53
Citations
16804
World Ranking
4711
National Ranking
2188

David Sontag 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 David Sontag 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: 159 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

David Sontag 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 David Sontag 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

David Sontag is affiliated with MIT in the United States and has a research profile spanning computer science and medicine. Their work integrates multiple disciplines with a strong emphasis on the intersection of artificial intelligence and healthcare.

The primary fields of study for David Sontag are:

  • Computer Science
  • Medicine

Their research delves into specialized subfields including:

  • Artificial Intelligence
  • Statistics and Probability
  • Molecular Biology
  • Rheumatology
  • Epidemiology

Key topics addressed in Sontag's publications include:

  • Machine Learning in Healthcare
  • Topic Modeling
  • Advanced Causal Inference Techniques
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques
  • Systemic Lupus Erythematosus Research
  • Biomedical Text Mining and Ontologies

Frequent coauthors in Sontag's collaborations are:

  • Michael Oberst
  • Monica Agrawal
  • Zeshan Hussain
  • Hussein Mozannar
  • Hunter Lang

The venues where David Sontag most often publishes include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Blood

Selected recent papers authored or coauthored by David Sontag include:

  • A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection, 2020, Science Translational Medicine
  • Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes, 2023, Annals of the Rheumatic Diseases
  • Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis, 2022, Nature Communications
  • The Potential For Bias In Machine Learning And Opportunities For Health Insurers To Address It, 2022, Health Affairs
  • TabLLM: Few-shot Classification of Tabular Data with Large Language Models, 2022, arXiv (Cornell University)

Best Publications

  • Recurrent Neural Networks for Multivariate Time Series with Missing Values.

    Zhengping Che;Sanjay Purushotham;Kyunghyun Cho;David A. Sontag

  • Character-aware neural language models

    Yoon Kim;Yacine Jernite;David Sontag;Alexander M. Rush

  • BLOG: Probabilistic Models with Unknown Objects

    Brian Milch;Bhaskara Marthi;Stuart Russell;David Sontag

  • Estimating individual treatment effect: generalization bounds and algorithms

    Uri Shalit;Fredrik D. Johansson;David A. Sontag

  • A Practical Algorithm for Topic Modeling with Provable Guarantees

    Sanjeev Arora;Rong Ge;Yonatan Halpern;David Mimno

  • Learning representations for counterfactual inference

    Fredrik D. Johansson;Uri Shalit;David Sontag

  • Structured Inference Networks for Nonlinear State Space Models

    Rahul G. Krishnan;Uri Shalit;David A. Sontag

  • Learning a Health Knowledge Graph from Electronic Medical Records.

    Maya Rotmensch;Yoni Halpern;Abdulhakim Tlimat;Steven Horng

  • Causal Effect Inference with Deep Latent-Variable Models

    Christos Louizos;Uri Shalit;Joris M. Mooij;David A. Sontag

  • Tightening LP relaxations for MAP using message passing

    David Sontag;Talya Meltzer;Amir Globerson;Tommi Jaakkola

  • Guidelines for reinforcement learning in healthcare

    Omer Gottesman;Fredrik Johansson;Matthieu Komorowski;Aldo Faisal

  • Large language models are few-shot clinical information extractors

    Unknown

  • Learning Low-Dimensional Representations of Medical Concepts.

    Youngduck Choi;Chill Yi-I Chiu;David A. Sontag

  • Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning

    Steven Horng;David A. Sontag;Yoni Halpern;Yacine Jernite

  • Unsupervised learning of disease progression models

    Xiang Wang;David Sontag;Fei Wang

  • On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing

    Alexander M Rush;David Sontag;Michael Collins;Tommi Jaakkola

  • Learning Bayesian Network Structure using LP Relaxations

    Tommi S. Jaakkola;David Alexander Sontag;Amir Globerson;Marina Meila

  • Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors.

    Narges Razavian;Saul Blecker;Ann Marie Schmidt;Aaron Smith-McLallen

  • Introduction to dual composition for inference

    David Sontag;Amir Globerson;Amir Globerson;Amir Globerson;Tommi Jaakkola

  • Deep Kalman Filters.

    Rahul G. Krishnan;Uri Shalit;David A. Sontag

  • Dual Decomposition for Parsing with Non-Projective Head Automata

    Terry Koo;Alexander M. Rush;Michael Collins;Tommi Jaakkola

Frequent Co-Authors

Amir Globerson
Amir Globerson Tel Aviv University
Alexander M. Rush
Alexander M. Rush Cornell University
Adrian Weller
Adrian Weller University of Cambridge
Paul N. Bennett
Paul N. Bennett Microsoft (United States)
Ryen W. White
Ryen W. White Microsoft (United States)
Kevyn Collins-Thompson
Kevyn Collins-Thompson University of Michigan–Ann Arbor
Rajesh Ranganath
Rajesh Ranganath New York University
Ann Marie Schmidt
Ann Marie Schmidt New York University

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