World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
12407
World Ranking
9511
National Ranking
4029

Ramesh Nallapati 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 Ramesh Nallapati 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: 93 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Ramesh Nallapati 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 Ramesh Nallapati 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Ramesh Nallapati is affiliated with Amazon in the United States and has an extensive publication record primarily in computer science. Their research spans multiple subfields, including artificial intelligence, computer vision and pattern recognition, information systems, statistical and nonlinear physics, as well as sociology and political science.

The scientist's research focuses on a range of topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, advanced text analysis techniques, software engineering research, machine learning and data classification, and complex network analysis techniques.

Notable recent papers by Ramesh Nallapati include:

  • Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs, 2021, Proceedings of the International AAAI Conference on Web and Social Media

Frequent co-authors in their work include:

  • Bing Xiang
  • Parminder Bhatia
  • Dejiao Zhang
  • Zhiguo Wang
  • Henghui Zhu

Ramesh Nallapati has published extensively in venues such as arXiv (Cornell University), with 24 publications, as well as in the Proceedings of the International AAAI Conference on Web and Social Media, the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, the Proceedings of the AAAI Conference on Artificial Intelligence, and the Findings of the Association for Computational Linguistics: NAACL 2022.

Best Publications

  • Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond

    Ramesh Nallapati;Bowen Zhou;Cicero Nogueira dos santos;Caglar Gulcehre

  • Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora

    Daniel Ramage;David Hall;Ramesh Nallapati;Christopher D. Manning

  • SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents

    Ramesh Nallapati;Feifei Zhai;Bowen Zhou

  • Multi-instance Multi-label Learning for Relation Extraction

    Mihai Surdeanu;Julie Tibshirani;Ramesh Nallapati;Christopher D. Manning

  • Pointing the unknown words

    Caglar Gulcehre;Sungjin Ahn;Ramesh Nallapati;Bowen Zhou

  • OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations

    Pramuditha Perera;Ramesh Nallapati;Bing Xiang

  • Joint latent topic models for text and citations

    Ramesh M. Nallapati;Amr Ahmed;Eric P. Xing;William W. Cohen

  • Discriminative models for information retrieval

    Ramesh Nallapati

  • Event threading within news topics

    Ramesh Nallapati;Ao Feng;Fuchun Peng;James Allan

  • A Comparative Study of Methods for Transductive Transfer Learning

    A. Arnold;R. Nallapati;W.W. Cohen

  • Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering

    Zhiguo Wang;Patrick Ng;Xiaofei Ma;Ramesh Nallapati

  • Sequence-to-Sequence RNNs for Text Summarization

    Ramesh Nallapati;Bing Xiang;Bowen Zhou

  • Link-PLSA-LDA: A New Unsupervised Model for Topics and Influence of Blogs.

    Ramesh Nallapati;William W. Cohen

  • Supporting Clustering with Contrastive Learning

    Dejiao Zhang;Feng Nan;Xiaokai Wei;Shang-Wen Li

  • A moving unstructured staggered mesh method for the simulation of incompressible free-surface flows

    Blair Perot;Ramesh Nallapati

  • Topic Modeling with Wasserstein Autoencoders

    Feng Nan;Ran Ding;Ramesh Nallapati;Bing Xiang

  • Classify or Select: Neural Architectures for Extractive Document Summarization

    Ramesh Nallapati;Bowen Zhou;Mingbo Ma

  • Capturing term dependencies using a language model based on sentence trees

    Ramesh Nallapati;James Allan

  • Elastic Machine Learning Algorithms in Amazon SageMaker

    Edo Liberty;Zohar Karnin;Bing Xiang;Laurence Rouesnel

  • Entity-level Factual Consistency of Abstractive Text Summarization.

    Feng Nan;Ramesh Nallapati;Zhiguo Wang;Cícero Nogueira dos Santos

  • Parallelized Variational EM for Latent Dirichlet Allocation: An Experimental Evaluation of Speed and Scalability

    Ramesh Nallapati;William Cohen;John Lafferty

Frequent Co-Authors

Bing Xiang
Bing Xiang Amazon (United States)
Bowen Zhou
Bowen Zhou IBM (United States)
Kathleen R. McKeown
Kathleen R. McKeown Columbia University
James Allan
James Allan University of Massachusetts Amherst
William W. Cohen
William W. Cohen Carnegie Mellon University
Christopher D. Manning
Christopher D. Manning Stanford University
Peng Xu
Peng Xu Chinese Academy of Sciences
Caglar Gulcehre
Caglar Gulcehre DeepMind (United Kingdom)
Mihai Surdeanu
Mihai Surdeanu University of Arizona
Chen Sun
Chen Sun Google (United States)

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