World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9522
World Ranking
4395
National Ranking
2052

Ashish Sabharwal 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 Ashish Sabharwal 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: 202 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Ashish Sabharwal 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 Ashish Sabharwal 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Ashish Sabharwal is a researcher affiliated with the Allen Institute for Artificial Intelligence in the United States. Their work spans the field of Computer Science, with a primary focus on Artificial Intelligence. The scientist has contributed extensively in various subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Electrical and Electronic Engineering.

The scientist's research topics cover several main areas, reflecting a broad engagement with both fundamental and applied aspects of machine learning and natural language processing. These topics include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Machine Learning and Algorithms
  • Software Engineering Research
  • Explainable Artificial Intelligence (XAI)
  • Semantic Web and Ontologies

Among recent publications, several papers stand out, illustrating a range of investigations into language models, dataset biases, and multimodal question answering. Some of these recent works are:

  • "Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models", 2022, arXiv (Cornell University)
  • "Adversarial Filters of Dataset Biases", 2020, arXiv (Cornell University)
  • " MuSiQue: Multihop Questions via Single-hop Question Composition", 2022, Transactions of the Association for Computational Linguistics
  • "Multi-Modal Answer Validation for Knowledge-Based VQA", 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Decomposed Prompting: A Modular Approach for Solving Complex Tasks", 2022, arXiv (Cornell University)

The scientist frequently publishes in several venues, with a significant number of their works appearing in the following:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • AI Magazine

Ashish Sabharwal collaborates regularly with several researchers, as indicated by repeated co-authorship. Notable frequent co-authors include:

  • Tushar Khot
  • Kyle Richardson
  • Peter Clark
  • Daniel Khashabi
  • Peter E. Clark

Best Publications

  • Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

    Peter Clark;Isaac Cowhey;Oren Etzioni;Tushar Khot

  • Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

    Todor Mihaylov;Peter Clark;Tushar Khot;Ashish Sabharwal

  • UNIFIEDQA: Crossing Format Boundaries with a Single QA System

    Daniel Khashabi;Sewon Min;Tushar Khot;Ashish Sabharwal

  • SciTaiL: A Textual Entailment Dataset from Science Question Answering

    Tushar Khot;Ashish Sabharwal;Peter Clark

  • Towards understanding and harnessing the potential of clause learning

    Paul Beame;Henry Kautz;Ashish Sabharwal

  • Decomposed Prompting: A Modular Approach for Solving Complex Tasks

    Unknown

  • Parsing Algebraic Word Problems into Equations

    Rik Koncel-Kedziorski;Hannaneh Hajishirzi;Ashish Sabharwal;Oren Etzioni

  • Complexity-Based Prompting for Multi-Step Reasoning

    Unknown

  • QASC: A dataset for question answering via sentence composition

    Tushar Khot;Peter Clark;Michal Guerquin;Peter Jansen

  • Chapter 2 Satisfiability Solvers

    Carla P. Gomes;Henry Kautz;Ashish Sabharwal;Bart Selman

  • Algorithm selection and scheduling

    Serdar Kadioglu;Yuri Malitsky;Ashish Sabharwal;Horst Samulowitz

  • Adversarial Filters of Dataset Biases

    Ronan Le Bras;Swabha Swayamdipta;Chandra Bhagavatula;Rowan Zellers

  • Model counting: a new strategy for obtaining good bounds

    Carla P. Gomes;Ashish Sabharwal;Bart Selman

  • Combining retrieval, statistics, and inference to answer elementary science questions

    Peter Clark;Oren Etzioni;Tushar Khot;Ashish Sabharwal

  • Probing Natural Language Inference Models through Semantic Fragments.

    Kyle Richardson;Hai Hu;Lawrence S. Moss;Ashish Sabharwal

  • Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints

    Carla P Gomes;Ashish Sabharwal;Bart Selman

  • Understanding the power of clause learning

    Paul Beanie;Henry Kautz;Ashish Sabharwal

  • Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization

    Stefano Ermon;Carla Gomes;Ashish Sabharwal;Bart Selman

  • From sampling to model counting

    Carla P. Gomes;Joerg Hoffmann;Ashish Sabharwal;Bart Selman

  • MuSiQue: Multi-hop Questions via Single-hop Question Composition

    Harsh Trivedi;Niranjan Balasubramanian;Tushar Khot;Ashish Sabharwal

  • Algorithm portfolios based on cost-sensitive hierarchical clustering

    Yuri Malitsky;Ashish Sabharwal;Horst Samulowitz;Meinolf Sellmann

  • Answering Complex Questions Using Open Information Extraction.

    Tushar Khot;Ashish Sabharwal;Peter Clark

  • UNQOVERing Stereotyping Biases via Underspecified Questions

    Tao Li;Daniel Khashabi;Tushar Khot;Ashish Sabharwal

Frequent Co-Authors

Carla P. Gomes
Carla P. Gomes Cornell University
Bart Selman
Bart Selman Cornell University
Peter Clark
Peter Clark Allen Institute for Artificial Intelligence
Daniel Khashabi
Daniel Khashabi Johns Hopkins University
Stefano Ermon
Stefano Ermon Stanford University
Paul Beame
Paul Beame University of Washington
Oren Etzioni
Oren Etzioni University of Washington
Dan Roth
Dan Roth University of Pennsylvania
Henry Kautz
Henry Kautz University of Virginia
Hannaneh Hajishirzi
Hannaneh Hajishirzi University of Washington

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