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D-Index & Metrics

Computer Science

D-Index
91
Citations
36759
World Ranking
579
National Ranking
309

Daniel Klein 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 Daniel Klein 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: 257 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Daniel Klein 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 Daniel Klein 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: 91 D-Index — 96th percentile

96% 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

  • 2007 - Fellow of Alfred P. Sloan Foundation
  • 2006 - Hellman Fellow
  • 2006 - ACM Grace Murray Hopper Award For the design of a system capable of learning a high-quality grammar for English directly from text.

Overview

Daniel Klein is affiliated with the University of California, Berkeley in the United States. Their research primarily spans the field of Computer Science, with a total of 149 publications documented. Within this domain, their work is notably concentrated in the subfields of Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Cognitive Neuroscience.

The scientist's research topics include Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Speech and Dialogue Systems, Text Readability and Simplification, Information and Cyber Security, and Speech Recognition and Synthesis.

Daniel Klein's frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • bioRxiv (Cold Spring Harbor Laboratory)

Their recent papers provide insight into the scope and impact of their research. Selected works include:

  • Multilingual Alignment of Contextual Word Representations, 2020, arXiv (Cornell University)
  • Constrained Language Models Yield Few-Shot Semantic Parsers, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Calibrate Before Use: Improving Few-Shot Performance of Language Models, 2021, arXiv (Cornell University)
  • Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers, 2020, arXiv (Cornell University)
  • Discovering Latent Knowledge in Language Models Without Supervision, 2022, arXiv (Cornell University)

Collaborations have been a significant aspect of Daniel Klein's research activities. Frequent co-authors include Ruiqi Zhong, Gal Engelberg, Giancarlo Guizzardi, Eve Fleisig, and Kevin Yang, each with multiple joint publications.

Throughout their career, Daniel Klein has received several awards, including the ACM Grace Murray Hopper Award in 2006, which recognized the design of a system capable of learning a high-quality grammar for English directly from text. The same year, they were named a Hellman Fellow. Additionally, in 2007, they were named a Fellow of the Alfred P. Sloan Foundation.

Best Publications

  • Feature-rich part-of-speech tagging with a cyclic dependency network

    Kristina Toutanova;Dan Klein;Christopher D. Manning;Yoram Singer

  • Accurate Unlexicalized Parsing

    Dan Klein;Christopher D. Manning

  • Abstractions for software architecture and tools to support them

    M. Shaw;R. DeLine;D.V. Klein;T.L. Ross

  • Neural Module Networks

    Jacob Andreas;Marcus Rohrbach;Trevor Darrell;Dan Klein

  • Fast Exact Inference with a Factored Model for Natural Language Parsing

    Dan Klein;Christopher D Manning

  • Learning Accurate, Compact, and Interpretable Tree Annotation

    Slav Petrov;Leon Barrett;Romain Thibaux;Dan Klein

  • From Instance-level Constraints to Space-Level Constraints: Making the Most of Prior Knowledge in Data Clustering

    Dan Klein;Sepandar D. Kamvar;Christopher D. Manning

  • Improved Inference for Unlexicalized Parsing

    Slav Petrov;Dan Klein

  • Learning Dependency-Based Compositional Semantics

    Percy Liang;Michael Jordan;Dan Klein

  • Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency

    Dan Klein;Christopher Manning

  • Constituency Parsing with a Self-Attentive Encoder

    Nikita Kitaev;Dan Klein

  • Learning to Compose Neural Networks for Question Answering

    Jacob Andreas;Marcus Rohrbach;Trevor Darrell;Dan Klein

  • Alignment by Agreement

    Percy Liang;Ben Taskar;Dan Klein

  • Foiling the cracker: A survey of, and improvements to, password security

    D.V. Klein

  • Spectral learning

    Sepandar D. Kamvar;Dan Klein;Christopher D. Manning

  • Abstract Syntax Networks for Code Generation and Semantic Parsing

    Maxim Rabinovich;Mitchell Stern;Dan Klein

  • Learning Bilingual Lexicons from Monolingual Corpora

    Aria Haghighi;Percy Liang;Taylor Berg-Kirkpatrick;Dan Klein

  • Speaker-Follower Models for Vision-and-Language Navigation

    Daniel Fried;Ronghang Hu;Volkan Cirik;Anna Rohrbach

  • An End-to-End Discriminative Approach to Machine Translation

    Percy Liang;Alexandre Bouchard-Côté;Dan Klein;Ben Taskar

  • Calibrate Before Use: Improving Few-shot Performance of Language Models

    Zihao Zhao;Eric Wallace;Shi Feng;Dan Klein

  • Learning Semantic Correspondences with Less Supervision

    Percy Liang;Michael Jordan;Dan Klein

  • Modular multitask reinforcement learning with policy sketches

    Jacob Andreas;Dan Klein;Sergey Levine

  • Calibrate Before Use: Improving Few-Shot Performance of Language Models

    Tony Z. Zhao;Eric Wallace;Shi Feng;Dan Klein

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