World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
97
Citations
39973
World Ranking
423
National Ranking
235

Lawrence Carin 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 Lawrence Carin 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: 816 publications — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Lawrence Carin 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 Lawrence Carin 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: 97 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Overview

Lawrence Carin is affiliated with Duke University in the United States and has a multidisciplinary research profile intersecting computer science and medicine. Their work spans a broad range of topics within artificial intelligence, machine learning, and medical imaging.

The scientist has produced significant contributions to fields including:

  • Computer Science
  • Medicine

Key subfields of study represented in their research include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Ophthalmology
  • Statistics and Probability

The main research topics Lawrence Carin focuses on involve:

  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Multimodal Machine Learning Applications
  • AI in cancer detection
  • Natural Language Processing Techniques
  • Radiomics and Machine Learning in Medical Imaging
  • Adversarial Robustness in Machine Learning

Their publication record includes work published in several prominent venues, with the most frequent being:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • UNC Libraries
  • IEEE Transactions on Neural Networks and Learning Systems
  • Scientific Reports

Recent papers by Lawrence Carin include:

  • Digital technology and COVID-19, 2020, Nature Medicine
  • What Makes Good In-Context Examples for GPT-3?, 2021, arXiv (Cornell University)
  • Convolutional neural network to identify symptomatic Alzheimer's disease using multimodal retinal imaging, 2020, British Journal of Ophthalmology
  • Application of a machine learning algorithm to predict malignancy in thyroid cytopathology, 2020, Cancer Cytopathology
  • SAGES consensus recommendations on an annotation framework for surgical video, 2021, Surgical Endoscopy

The scientist has collaborated frequently with a number of co-authors, including:

  • Ricardo Henao (40 publications)
  • David Dov (18 publications)
  • Chenyang Tao (15 publications)
  • Zhe Gan (11 publications)
  • Kevin J Liang (11 publications)

Best Publications

  • Bayesian Compressive Sensing

    Shihao Ji;Ya Xue;L. Carin

  • Digital technology and COVID-19.

    Daniel Shu Wei Ting;Lawrence Carin;Victor Dzau;Victor Dzau;Tien Y. Wong

  • Sparse multinomial logistic regression: fast algorithms and generalization bounds

    B. Krishnapuram;L. Carin;M.A.T. Figueiredo;A.J. Hartemink

  • Variational autoencoder for deep learning of images, labels and captions

    Yunchen Pu;Zhe Gan;Ricardo Henao;Xin Yuan

  • Multi-Task Learning for Classification with Dirichlet Process Priors

    Ya Xue;Xuejun Liao;Lawrence Carin;Balaji Krishnapuram

  • Multitask Compressive Sensing

    S. Ji;D. Dunson;L. Carin

  • Compressive Coded Aperture Spectral Imaging: An Introduction

    Gonzalo R. Arce;David J. Brady;Lawrence Carin;Henry Arguello

  • Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing

    Lihan He;L. Carin

  • An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis

    Raymond J. Langley;Raymond J. Langley;Ephraim L. Tsalik;Ephraim L. Tsalik;Jennifer C. Van Velkinburgh;Seth W. Glickman;Seth W. Glickman

  • Coded aperture compressive temporal imaging

    Patrick Llull;Xuejun Liao;Xin Yuan;Jianbo Yang

  • Semantic Compositional Networks for Visual Captioning

    Zhe Gan;Chuang Gan;Xiaodong He;Yunchen Pu

  • Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

    Mingyuan Zhou;Haojun Chen;John Paisley;Lu Ren

  • Probabilistic Topic Models

    David Blei;Lawrence Carin;David Dunson

  • What Makes Good In-Context Examples for GPT-3?

    Jiachang Liu;Dinghan Shen;Yizhe Zhang;Bill Dolan

  • Joint Embedding of Words and Labels for Text Classification

    Guoyin Wang;Chunyuan Li;Wenlin Wang;Yizhe Zhang

  • Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing

    Hao Fu;Chunyuan Li;Xiaodong Liu;Jianfeng Gao

  • Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

    Dinghan Shen;Guoyin Wang;Wenlin Wang;Martin Renqiang Min

  • Nonparametric factor analysis with beta process priors

    John Paisley;Lawrence Carin

  • Bayesian Robust Principal Component Analysis

    Xinghao Ding;Lihan He;L. Carin

  • Certified Adversarial Robustness with Additive Noise

    Bai Li;Changyou Chen;Wenlin Wang;Lawrence Carin

  • Multi-Task Compressive Sensing

    Shihao Ji;David Dunson;Lawrence Carin

Frequent Co-Authors

Zhe Gan
Zhe Gan Microsoft (United States)
David B. Dunson
David B. Dunson Duke University
Xin Yuan
Xin Yuan Nanyang Technological University
Chunyuan Li
Chunyuan Li Microsoft (United States)
David J. Brady
David J. Brady University of Arizona
Liqun Chen
Liqun Chen University of Surrey
Guillermo Sapiro
Guillermo Sapiro Princeton University
Mingyuan Zhou
Mingyuan Zhou The University of Texas at Austin
Guoyin Wang
Guoyin Wang Chongqing University of Posts and Telecommunications
John Paisley
John Paisley Columbia University

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