World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9534
World Ranking
7493
National Ranking
3260

Yan Huang 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 Yan Huang 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: 244 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Yan Huang 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 Yan Huang 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Yan Huang is affiliated with the University of North Texas in the United States. Their research primarily spans the fields of Computer Science and Engineering, with a substantial focus on Artificial Intelligence, explored in 45 publications, along with contributions to Sociology and Political Science, Computer Science Applications, Electrical and Electronic Engineering, and Information Systems.

Their work addresses several specialized topics, including:

  • Privacy-Preserving Technologies in Data
  • Mobile Crowdsensing and Crowdsourcing
  • Adversarial Robustness in Machine Learning
  • Cryptography and Data Security
  • Privacy, Security, and Data Protection
  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques

Yan Huang has published in multiple venues, with notable contributions to:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • High-Confidence Computing
  • Future Generation Computer Systems
  • Big Data Mining and Analytics

Frequent collaborators include:

  • Zhenzhen Xie (9 joint publications)
  • Junjie Pang (8 joint publications)
  • Zhipeng Cai (6 joint publications)
  • Liang Wang (3 joint publications)
  • Reza M. Parizi (2 joint publications)

Among recent research outputs, several papers highlight the scope and evolution of Yan Huang's work:

  • A survey on security and privacy of federated learning, 2020, Future Generation Computer Systems
  • Security and Privacy in Metaverse: A Comprehensive Survey, 2023, Big Data Mining and Analytics
  • Realizing the Heterogeneity: A Self-Organized Federated Learning Framework for IoT, 2020, IEEE Internet of Things Journal
  • Exploring personalization via federated representation Learning on non-IID data, 2023, Neural Networks
  • Computational Approaches to Detect Illicit Drug Ads and Find Vendor Communities Within Social Media Platforms, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics

The research emphasis on privacy, security, and federated learning is evident, illustrated by topics such as personalized learning on non-IID data and privacy-preserving mechanisms in decentralized environments. Yan Huang's studies also cover the intersection of machine learning with social and biological data contexts, as indicated by their work on illicit drug ad detection via computational methods.

Best Publications

  • T-drive: driving directions based on taxi trajectories

    Jing Yuan;Yu Zheng;Chengyang Zhang;Wenlei Xie

  • Map-matching for low-sampling-rate GPS trajectories

    Yin Lou;Chengyang Zhang;Yu Zheng;Xing Xie

  • Discovering colocation patterns from spatial data sets: a general approach

    Y. Huang;S. Shekhar;H. Xiong

  • Advances in Spatial and Temporal Databases

    Michael Gertz;Matthias Renz;Xiaofang Zhou;Erik Hoel

  • Discovering Spatial Co-location Patterns: A Summary of Results

    Shashi Shekhar;Yan Huang

  • Digital game-based vocabulary learning: where are we and where are we going?

    Di Zou;Yan Huang;Haoran Xie

  • Efficient Privacy-Preserving Biometric Identification

    Yan Huang;Lior Malka;David Evans;Jonathan Katz

  • Mining Co-Location Patterns with Rare Events from Spatial Data Sets

    Yan Huang;Jian Pei;Hui Xiong

  • Propagation networks for recognition of partially ordered sequential action

    Yifan Shi;Yan Huang;D. Minnen;A. Bobick

  • Large scale real-time ridesharing with service guarantee on road networks

    Yan Huang;Favyen Bastani;Ruoming Jin;Xiaoyang Sean Wang

  • A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets

    Yan Huang;Liqin Zhang;Pusheng Zhang

  • Towards reducing taxicab cruising time using spatio-temporal profitability maps

    Jason W. Powell;Yan Huang;Favyen Bastani;Minhe Ji

  • Evacuation planning: a capacity constrained routing approach

    Qingsong Lu;Yan Huang;Shashi Shekhar

  • A Framework for Discovering Co-location Patterns in Data Sets with Extended Spatial Objects

    Hui Xiong;Shashi Shekhar;Yan Huang;Vipin Kumar

  • Mining confident co-location rules without a support threshold

    Yan Huang;Hui Xiong;Shashi Shekhar;Jian Pei

  • Terahertz emission and detection both based on high-Tc superconductors: Towards an integrated receiver

    D. Y. An;J. Yuan;N. Kinev;M. Y. Li

  • Discovering Co-location Patterns from Spatial Datasets: A General Approach

    Yan Huang;Shashi Shekhar;Hui Xiong

  • Notice of Removal: VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

    Unknown

  • Relational Network for Skeleton-Based Action Recognition

    Wu Zheng;Lin Li;Zhaoxiang Zhang;Yan Huang

  • Integration of wireless sensor networks in environmental monitoring cyber infrastructure

    Jue Yang;Chengyang Zhang;Xinrong Li;Yan Huang

  • Cloaking locations for anonymous location based services: a hybrid approach

    Chengyang Zhang;Yan Huang

  • Semi-Supervised GMM and DNN Acoustic Model Training with Multi-system Combination and Confidence Re-calibration

    Yan Huang;Dong Yu;Yifan Gong;Chaojun Liu

  • On the Relationships between Clustering and Spatial Co-location Pattern Mining

    Yan Huang;Pusheng Zhang

  • SPOT: locating social media users based on social network context

    Longbo Kong;Zhi Liu;Yan Huang

  • Multi-pseudo Regularized Label for Generated Samples in Person Re-Identification

    Yan Huang;Jinsong Xu;Qiang Wu;Zhedong Zheng

Frequent Co-Authors

Yifan Gong
Yifan Gong Microsoft (United States)
Shashi Shekhar
Shashi Shekhar University of Minnesota
Jinyu Li
Jinyu Li Microsoft (United States)
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Quanxing Zhang
Quanxing Zhang Nanjing University
Jean-Claude Thill
Jean-Claude Thill University of North Carolina at Charlotte
Miaogen Shen
Miaogen Shen Chinese Academy of Sciences
Xiaoshuang Chen
Xiaoshuang Chen Chinese Academy of Sciences
Ruoming Jin
Ruoming Jin Kent State University
Bill P. Buckles
Bill P. Buckles University of North Texas

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