World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
8575
World Ranking
7184
National Ranking
3142

Liangliang Cao 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 Liangliang Cao 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: 163 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Liangliang Cao 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 Liangliang Cao 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: 45 D-Index — 51st percentile

51% 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

  • 2020 - ACM Senior Member

Overview

Liangliang Cao is affiliated with Google in the United States and has a research portfolio concentrated primarily in the field of Computer Science. Their work spans diverse subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Graphics and Computer-Aided Design, and Computational Mechanics.

The scientist's research topics include:

  • Speech Recognition and Synthesis
  • Topic Modeling
  • Music and Audio Processing
  • Speech and Audio Processing
  • Natural Language Processing Techniques
  • Computer Graphics and Visualization Techniques
  • 3D Shape Modeling and Analysis

Several recent papers illustrate the breadth of Cao's research contributions. These include:

  • BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition, 2022, IEEE Journal of Selected Topics in Signal Processing
  • Microfluidic-based exosome isolation and highly sensitive aptamer exosome membrane protein detection for lung cancer diagnosis, 2022, Biosensors and Bioelectronics
  • Ferret: Refer and Ground Anything Anywhere at Any Granularity, 2023, arXiv (Cornell University)
  • Diffusion Model-Based Image Editing: A Survey, 2025, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Product image recognition with guidance learning and noisy supervision, 2020, Computer Vision and Image Understanding

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • IEEE Journal of Selected Topics in Signal Processing
  • Biosensors and Bioelectronics
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Computer Vision and Image Understanding

Notable frequent co-authors include Yu Zhang, Ruoming Pang, Qiujia Li, Wei Han, and David Qiu.

In 2020, Liangliang Cao was recognized as an ACM Senior Member.

Best Publications

  • Learning from Noisy Labels with Distillation

    Yuncheng Li;Jianchao Yang;Yale Song;Liangliang Cao

  • Large-scale image classification: Fast feature extraction and SVM training

    Yuanqing Lin;Fengjun Lv;Shenghuo Zhu;Ming Yang

  • Spatially Coherent Latent Topic Model for Concurrent Segmentation and Classification of Objects and Scenes

    Liangliang Cao;Li Fei-Fei

  • Learning Locally-Adaptive Decision Functions for Person Verification

    Zhen Li;Shiyu Chang;Feng Liang;Thomas S. Huang

  • Geographical topic discovery and comparison

    Zhijun Yin;Liangliang Cao;Jiawei Han;Chengxiang Zhai

  • Cross-dataset action detection

    Liangliang Cao;Zicheng Liu;Thomas S. Huang

  • Mining Fashion Outfit Composition Using an End-to-End Deep Learning Approach on Set Data

    Yuncheng Li;Liangliang Cao;Jiang Zhu;Jiebo Luo

  • Designing Category-Level Attributes for Discriminative Visual Recognition

    Felix X. Yu;Liangliang Cao;Rogerio S. Feris;John R. Smith

  • TGIF: A New Dataset and Benchmark on Animated GIF Description

    Yuncheng Li;Yale Song;Liangliang Cao;Joel Tetreault

  • Action detection in complex scenes with spatial and temporal ambiguities

    Yuxiao Hu;Liangliang Cao;Fengjun Lv;Shuicheng Yan

  • Detecting Sarcasm in Multimodal Social Platforms

    Rossano Schifanella;Paloma de Juan;Joel Tetreault;LiangLiang Cao

  • Gender recognition from body

    Liangliang Cao;Mert Dikmen;Yun Fu;Thomas S. Huang

  • The wisdom of social multimedia: using flickr for prediction and forecast

    Xin Jin;Andrew Gallagher;Liangliang Cao;Jiebo Luo

  • Aworldwide tourism recommendation system based on geotaggedweb photos

    Liangliang Cao;Jiebo Luo;Andrew Gallagher;Xin Jin

  • Automatic Adaptation of Object Detectors to New Domains Using Self-Training

    Aruni RoyChowdhury;Prithvijit Chakrabarty;Ashish Singh;SouYoung Jin

  • Video2GIF: Automatic Generation of Animated GIFs from Video

    Michael Gygli;Yale Song;Liangliang Cao

  • BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

    Yu Zhang;Daniel S. Park;Wei Han;James Qin

  • Multiple feature fusion by subspace learning

    Yun Fu;Liangliang Cao;Guodong Guo;Thomas S. Huang

  • Diversified Trajectory Pattern Ranking in Geo-Tagged Social Media

    Zhijun Yin;Liangliang Cao;Jiawei Han;Jiebo Luo

  • Latent Community Topic Analysis: Integration of Community Discovery with Topic Modeling

    Zhijun Yin;Liangliang Cao;Quanquan Gu;Jiawei Han

  • Additional Remarks on Designing Category-Level Attributes for Discriminative Visual Recognition

    Felix X Yu;Liangliang Cao;Rogerio S Feris;John R Smith

Frequent Co-Authors

Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Jiebo Luo
Jiebo Luo University of Rochester
John R. Smith
John R. Smith IBM (United States)
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Jianzhuang Liu
Jianzhuang Liu Shenzhen Institutes of Advanced Technology
Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Gang Hua
Gang Hua Dolby (United States)
Rogerio Feris
Rogerio Feris IBM (United States)
Chung-Cheng Chiu
Chung-Cheng Chiu Google (United States)
Shih-Fu Chang
Shih-Fu Chang Columbia University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA often leads students to consider flexible online options. Many learners are searching for cheap online degrees fast to save money and time. Accelerated programs, such as a 2-year computer science degree online, allow students to launch tech careers swiftly without sacrificing quality.

For those concerned about past academic performance, don’t worry—there are reputable online colleges that accept 2.0 gpa. This makes computer science degrees accessible to more students, regardless of GPA.

Studying computer science also opens doors to diverse tech roles. However, don’t overlook multidisciplinary options. For instance, combining tech with a passion for sustainability can create pathways to jobs for environmental science majors. Choosing the right program and career path depends on your goals, interests, and schedule—there’s an option to fit every background and ambition.

Best Scientists Citing Liangliang Cao

Trending Scientists

Recently Published Articles