World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
87046
World Ranking
9004
National Ranking
3820

Li-Jia Li 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 Li-Jia Li 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: 54 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

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

Li-Jia Li 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 Li-Jia Li 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Li-Jia Li is affiliated with Stanford University in the United States and has contributed extensively to the intersection of computer science and medicine. Their research spans a range of topics primarily focused on artificial intelligence and its applications in healthcare and education.

The scientist has a significant number of publications in reputable venues. Among the frequent publication outlets are:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • npj Digital Medicine
  • Ultrasonics Sonochemistry
  • Advances in Nutrition

Li-Jia Li's main fields of study include:

  • Computer Science
  • Medicine

The research covers several subfields, with a focus on:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Biomedical Engineering
  • Health Informatics

Key topics addressed in their publications include:

  • Topic Modeling
  • Artificial Intelligence in Healthcare and Education
  • Machine Learning in Healthcare
  • Acute Ischemic Stroke Management
  • Cognitive and developmental aspects of mathematical skills
  • Medical Imaging and Analysis
  • Advanced X-ray and CT Imaging

Some recent papers authored or co-authored by Li-Jia Li are:

  • Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI, 2024, npj Digital Medicine
  • Comparison of soy protein isolate-(-)-epigallocatechin gallate complexes prepared by mixing, chemical polymerization, and ultrasound treatment, 2022, Ultrasonics Sonochemistry
  • CoCo: Controllable Counterfactuals for Evaluating Dialogue State Trackers, 2020, arXiv (Cornell University)
  • A Scoping Review of Artificial Intelligence for Precision Nutrition, 2025, Advances in Nutrition
  • Exploring students' procedural flexibility in three countries, 2022, International Journal of STEM Education

Li-Jia Li frequently collaborates with a group of co-authors, including:

  • Sophie Ostmeier
  • Brian Axelrod
  • Jeremy J. Heit
  • David Oniani
  • Yanshan Wang

Best Publications

  • ImageNet: A large-scale hierarchical image database

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

  • Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

    Ranjay Krishna;Yuke Zhu;Oliver Groth;Justin Johnson

  • Progressive Neural Architecture Search

    Chenxi Liu;Barret Zoph;Maxim Neumann;Jonathon Shlens

  • YFCC100M: the new data in multimedia research

    Bart Thomee;David A. Shamma;Gerald Friedland;Benjamin Elizalde

  • AMC: AutoML for Model Compression and Acceleration on Mobile Devices

    Yihui He;Ji Lin;Zhijian Liu;Hanrui Wang

  • Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification

    Li-jia Li;Hao Su;Li Fei-fei;Eric P. Xing

  • Image retrieval using scene graphs

    Justin Johnson;Ranjay Krishna;Michael Stark;Li-Jia Li

  • What, where and who? Classifying events by scene and object recognition

    Li-Jia Li;Li Fei-Fei

  • MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels

    Lu Jiang;Zhengyuan Zhou;Thomas Leung;Li-Jia Li

  • Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

    Ranjay Krishna;Yuke Zhu;Oliver Groth;Justin Johnson

  • Multi-view Face Detection Using Deep Convolutional Neural Networks

    Sachin Sudhakar Farfade;Mohammad J. Saberian;Li-Jia Li

  • Towards total scene understanding: Classification, annotation and segmentation in an automatic framework

    Li-Jia Li;Richard Socher;Li Fei-Fei

  • Learning from Noisy Labels with Distillation

    Yuncheng Li;Jianchao Yang;Yale Song;Liangliang Cao

  • Thoracic Disease Identification and Localization with Limited Supervision

    Zhe Li;Chong Wang;Mei Han;Yuan Xue

  • The New Data and New Challenges in Multimedia Research.

    Bart Thomee;David A. Shamma;Gerald Friedland;Benjamin Elizalde

  • Composing Text and Image for Image Retrieval - an Empirical Odyssey

    Nam Vo;Lu Jiang;Chen Sun;Kevin Murphy

  • Deep Reinforcement Learning-Based Image Captioning with Embedding Reward

    Zhou Ren;Xiaoyu Wang;Ning Zhang;Xutao Lv

  • OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning

    Li-Jia Li;Gang Wang;Li Fei-Fei

  • Attention-based Graph Neural Network for Semi-supervised Learning

    Kiran Koshy Thekumparampil;Chong Wang;Sewoong Oh;Li-Jia Li

  • Best of both worlds: Human-machine collaboration for object annotation

    Olga Russakovsky;Li-Jia Li;Li Fei-Fei

  • Eidetic 3D LSTM: A Model for Video Prediction and Beyond

    Yunbo Wang;Yunbo Wang;Lu Jiang;Ming Hsuan Yang;Li Jia Li

Frequent Co-Authors

Li Fei-Fei
Li Fei-Fei Stanford University
Jia Deng
Jia Deng Princeton University
Liangliang Cao
Liangliang Cao Google (United States)
Xiangnan Kong
Xiangnan Kong Worcester Polytechnic Institute
Jianchao Yang
Jianchao Yang ByteDance
Hao Su
Hao Su University of California, San Diego
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Michael S. Bernstein
Michael S. Bernstein Stanford University
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Gerald Friedland
Gerald Friedland Yale University

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