World's Best Scientists 2026 revealed!
Richard Socher

Richard Socher

D-Index & Metrics

Computer Science

D-Index
90
Citations
160587
World Ranking
588
National Ranking
315

Richard Socher 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 Richard Socher 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: 213 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Richard Socher 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 Richard Socher 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: 90 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.

Overview

Richard Socher is affiliated with you.com in the United States and specializes primarily in computer science, with a research focus on artificial intelligence. Their work spans multiple subfields, including molecular biology, computer vision and pattern recognition, radiology, nuclear medicine and imaging, as well as sociology and political science.

The main topics of Socher's research include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • AI in Cancer Detection
  • Machine Learning in Bioinformatics
  • Neural Networks and Applications
  • Domain Adaptation and Few-Shot Learning

Socher has contributed extensively to scientific literature, with a total of 109 publications in computer science and related fields. Frequent publication venues include:

  • arXiv (Cornell University)
  • npj Digital Medicine
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Biotechnology
  • Chemical Science

Some recent papers featuring Socher's work are:

  • Deep learning-enabled medical computer vision, 2021, npj Digital Medicine
  • Large language models generate functional protein sequences across diverse families, 2023, Nature Biotechnology
  • DivideMix: Learning with Noisy Labels as Semi-supervised Learning, 2020, arXiv (Cornell University)
  • Prototypical Contrastive Learning of Unsupervised Representations, 2020, arXiv (Cornell University)
  • Dye-sensitized solar cells under ambient light powering machine learning: towards autonomous smart sensors for the internet of things, 2020, Chemical Science

Frequent collaborators in Socher's research include:

  • Caiming Xiong
  • Andre Esteva
  • Nikhil Naik
  • Ali Madani
  • Steven C. H. Hoi

Best Publications

  • ImageNet: A large-scale hierarchical image database

    Jia Deng;Wei Dong;Richard Socher;Li-Jia Li

  • Glove: Global Vectors for Word Representation

    Jeffrey Pennington;Richard Socher;Christopher Manning

  • Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

    Richard Socher;Alex Perelygin;Jean Wu;Jason Chuang

  • Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

    Kai Sheng Tai;Richard Socher;Christopher D. Manning

  • Reasoning With Neural Tensor Networks for Knowledge Base Completion

    Richard Socher;Danqi Chen;Christopher D Manning;Andrew Ng

  • Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning

    Jiasen Lu;Caiming Xiong;Devi Parikh;Richard Socher

  • Parsing Natural Scenes and Natural Language with Recursive Neural Networks

    Richard Socher;Cliff C. Lin;Chris Manning;Andrew Y. Ng

  • Semantic Compositionality through Recursive Matrix-Vector Spaces

    Richard Socher;Brody Huval;Christopher D. Manning;Andrew Y. Ng

  • Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions

    Richard Socher;Jeffrey Pennington;Eric H. Huang;Andrew Y. Ng

  • A Deep Reinforced Model for Abstractive Summarization

    Romain Paulus;Caiming Xiong;Richard Socher

  • Improving Word Representations via Global Context and Multiple Word Prototypes

    Eric Huang;Richard Socher;Christopher Manning;Andrew Ng

  • Zero-Shot Learning Through Cross-Modal Transfer

    Richard Socher;Milind Ganjoo;Christopher D Manning;Andrew Ng

  • Ask me anything: dynamic memory networks for natural language processing

    Ankit Kumar;Ozan Irsoy;Peter Ondruska;Mohit Iyyer

  • Deep learning-enabled medical computer vision.

    Andre Esteva;Katherine Chou;Serena Yeung;Nikhil Naik

  • Parsing with Compositional Vector Grammars

    Richard Socher;John Bauer;Christopher D. Manning;Ng Andrew Y.

  • Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

    Victor Zhong;Caiming Xiong;Richard Socher

  • Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection

    Richard Socher;Eric H. Huang;Jeffrey Pennin;Christopher D Manning

  • CTRL: A Conditional Transformer Language Model for Controllable Generation

    Nitish Shirish Keskar;Bryan McCann;Lav R. Varshney;Caiming Xiong

  • Zero-Shot Learning Through Cross-Modal Transfer

    Richard Socher;Milind Ganjoo;Hamsa Sridhar;Osbert Bastani

  • Grounded Compositional Semantics for Finding and Describing Images with Sentences

    Richard Socher;Andrej Karpathy;Quoc V. Le;Christopher D. Manning

  • Better Word Representations with Recursive Neural Networks for Morphology

    Thang Luong;Richard Socher;Christopher Manning

Frequent Co-Authors

Caiming Xiong
Caiming Xiong Salesforce (United States)
Christopher D. Manning
Christopher D. Manning Stanford University
Andrew Y. Ng
Andrew Y. Ng Stanford University
Steven C. H. Hoi
Steven C. H. Hoi Alibaba Group (China)
Dragomir R. Radev
Dragomir R. Radev Yale University
Lav R. Varshney
Lav R. Varshney University of Illinois at Urbana-Champaign
Larry S. Davis
Larry S. Davis University of Maryland, College Park
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Shafiq Joty
Shafiq Joty Salesforce (United States)
Zuxuan Wu
Zuxuan Wu Fudan University

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