World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
14621
World Ranking
3605
National Ranking
1731

Jacob Eisenstein 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 Jacob Eisenstein 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: 168 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Jacob Eisenstein 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 Jacob Eisenstein 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

Jacob Eisenstein is a researcher affiliated with Google in the United States, specializing in the field of Computer Science with a focus on Artificial Intelligence. Their scholarly contributions span multiple subfields including Computer Vision and Pattern Recognition, Sociology and Political Science, General Social Sciences, and Statistical and Nonlinear Physics.

The main topics covered in their work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Explainable Artificial Intelligence (XAI)
  • Multimodal Machine Learning Applications
  • Machine Learning and Algorithms
  • Computational and Text Analysis Methods
  • Complex Network Analysis Techniques

Jacob Eisenstein has been published extensively, with a significant number of papers appearing in venues such as:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Journal of Cultural Analytics

Some of their recent papers include:

  • Underspecification Presents Challenges for Credibility in Modern Machine Learning, 2020, arXiv (Cornell University)
  • Sparse, Dense, and Attentional Representations for Text Retrieval, 2021, Transactions of the Association for Computational Linguistics
  • Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond, 2022, Transactions of the Association for Computational Linguistics
  • Sparse, Dense, and Attentional Representations for Text Retrieval, 2020, arXiv (Cornell University)
  • Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer, 2021, arXiv (Cornell University)

Throughout their research career, Jacob Eisenstein has collaborated frequently with a group of co-authors. Those with the most joint publications include:

  • Jonathan Berant
  • Victor Veitch
  • Chirag Nagpal
  • Kristina Toutanova
  • Diyi Yang

The focus areas of Eisenstein's work reflect a broad interdisciplinary approach, incorporating elements of artificial intelligence techniques and the social sciences. This multidisciplinary perspective is evident in their publication record and chosen research topics.

Best Publications

  • Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments

    Kevin Gimpel;Nathan Schneider;Brendan O'Connor;Dipanjan Das

  • A Latent Variable Model for Geographic Lexical Variation

    Jacob Eisenstein;Brendan O'Connor;Noah A. Smith;Eric P. Xing

  • Gender identity and lexical variation in social media

    David Bamman;Jacob Eisenstein;Tyler Schnoebelen

  • Explainable Prediction of Medical Codes from Clinical Text

    James Mullenbach;Sarah Wiegreffe;Jon Duke;Jimeng Sun

  • Underspecification Presents Challenges for Credibility in Modern Machine Learning

    Alexander D'Amour;Katherine A. Heller;Dan Moldovan;Ben Adlam

  • You Can't Stay Here: The Efficacy of Reddit's 2015 Ban Examined Through Hate Speech

    Eshwar Chandrasekharan;Umashanthi Pavalanathan;Anirudh Srinivasan;Adam Glynn

  • What to do about bad language on the internet

    Jacob Eisenstein

  • Sparse Additive Generative Models of Text

    Jacob Eisenstein;Amr Ahmed;Eric P. Xing

  • Applying model-based techniques to the development of UIs for mobile computers

    Jacob Eisenstein;Jean Vanderdonckt;Angel Puerta

  • Towards a general computational framework for model-based interface development systems

    Angel R. Puerta;Jacob Eisenstein

  • The Internet's Hidden Rules: An Empirical Study of Reddit Norm Violations at Micro, Meso, and Macro Scales

    Eshwar Chandrasekharan;Mattia Samory;Shagun Jhaver;Hunter Charvat

  • Bayesian Unsupervised Topic Segmentation

    Jacob Eisenstein;Regina Barzilay

  • Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond

    Unknown

  • Representation Learning for Text-level Discourse Parsing

    Yangfeng Ji;Jacob Eisenstein

  • Diffusion of lexical change in social media.

    Jacob Eisenstein;Brendan O'Connor;Noah A. Smith;Eric P. Xing

  • Sparse, Dense, and Attentional Representations for Text Retrieval

    Yi Luan;Jacob Eisenstein;Kristina Toutanova;Michael Collins

  • Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics

    Kevin Gimpel;Nathan Schneider;Brendan O'Connor;Dipanjan Das

  • XIML: a common representation for interaction data

    Angel Puerta;Jacob Eisenstein

  • Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling

    Xiaochuang Han;Jacob Eisenstein

  • Better Document-level Sentiment Analysis from RST Discourse Parsing

    Parminder Bhatia;Yangfeng Ji;Jacob Eisenstein

  • Discriminative Improvements to Distributional Sentence Similarity

    Yangfeng Ji;Jacob Eisenstein

Frequent Co-Authors

Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Noah A. Smith
Noah A. Smith University of Washington
Maria Liakata
Maria Liakata Queen Mary University of London
Diyi Yang
Diyi Yang Stanford University
Jimeng Sun
Jimeng Sun University of Illinois at Urbana-Champaign
Sharon Goldwater
Sharon Goldwater University of Edinburgh
Cyrus Shahabi
Cyrus Shahabi University of Southern California
Munmun De Choudhury
Munmun De Choudhury Georgia Institute of Technology

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