World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
4857
World Ranking
11342
National Ranking
1390

Gang 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 Gang 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: 227 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Gang 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 Gang 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Gang Huang is affiliated with Peking University in China and has contributed extensively to the field of computer science, with a strong focus on information systems, artificial intelligence, computer networks and communications, computer vision and pattern recognition, and aerospace engineering.

Their research explores diverse topics including IoT and edge/fog computing, privacy-preserving technologies in data, blockchain technology applications and security, advanced neural network applications, cloud computing and resource management, software system performance and reliability, and software engineering research.

Frequent coauthors collaborating with Gang Huang include Xuanzhe Liu, Yun Ma, Haoyu Wang, Mengwei Xu, and Xin Jin.

Gang Huang's recent publications include:

  • Federated Learning on Heterogeneous and Long-Tailed Data via Classifier Re-Training with Federated Features (2022), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • The Case for FPGA-Based Edge Computing (2020), IEEE Transactions on Mobile Computing
  • Sex-related Differences in Inflammatory Bowel Diseases: The Potential Role of Sex Hormones (2022), Inflammatory Bowel Diseases
  • Altered Gut Microbiota in Patients With Peutz-Jeghers Syndrome (2022), Frontiers in Microbiology
  • FLASH: Heterogeneity-Aware Federated Learning at Scale (2022), IEEE Transactions on Mobile Computing

Gang Huang has published predominantly in venues such as arXiv (Cornell University), IEEE Transactions on Mobile Computing, ACM Transactions on Software Engineering and Methodology, Signal Image and Video Processing, and IEEE Transactions on Services Computing.

Best Publications

  • Precise condition synthesis for program repair

    Yingfei Xiong;Jie Wang;Runfa Yan;Jiachen Zhang

  • Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users

    Xuan Lu;Wei Ai;Xuanzhe Liu;Qian Li

  • Refactoring android Java code for on-demand computation offloading

    Ying Zhang;Gang Huang;Xuanzhe Liu;Wei Zhang

  • Identifying patch correctness in test-based program repair

    Yingfei Xiong;Xinyuan Liu;Muhan Zeng;Lu Zhang

  • A first look at blockchain-based decentralized applications

    Kaidong Wu;Yun Ma;Gang Huang;Xuanzhe Liu

  • Discovering Homogeneous Web Service Community in the User-Centric Web Environment

    Xuanzhe Liu;Gang Huang;Hong Mei

  • Runtime recovery and manipulation of software architecture of component-based systems

    Gang Huang;Hong Mei;Fu-Qing Yang

  • Internetware: A Software Paradigm for Internet Computing

    Hong Mei;Gang Huang;Tao Xie

  • Runtime model based approach to IoT application development

    Xing Chen;Aipeng Li;Xue'e Zeng;Wenzhong Guo

  • Supporting runtime software architecture: A bidirectional-transformation-based approach

    Hui Song;Gang Huang;Franck Chauvel;Yingfei Xiong

  • Untangling emoji popularity through semantic embeddings

    Wei Ai;Xuan Lu;Xuanzhe Liu;Ning Wang

  • A software architecture centric engineering approach for Internetware

    Hong Mei;Gang Huang;Haiyan Zhao;Wenpin Jiao

  • PKUAS: an architecture-based reflective component operating platform

    Hong Mei;Gang Huang

  • Model-Based Automated Navigation and Composition of Complex Service Mashups

    Gang Huang;Yun Ma;Xuanzhe Liu;Yuchong Luo

  • Integrating Resource Consumption and Allocation for Infrastructure Resources on-Demand

    Ying Zhang;Gang Huang;Xuanzhe Liu;Hong Mei

  • MALMOS: Machine Learning-Based Mobile Offloading Scheduler with Online Training

    Heungsik Eom;Renato Figueiredo;Huaqian Cai;Ying Zhang

  • Towards autonomic computing middleware via reflection

    Gang Huang;Tiancheng Liu;Hong Mei;Zizhan Zheng

  • ShuffleDog: Characterizing and Adapting User-Perceived Latency of Android Apps

    Gang Huang;Mengwei Xu;Felix Xiaozhu Lin;Yunxin Liu

  • An empirical study on challenges of application development in serverless computing

    Jinfeng Wen;Zhenpeng Chen;Yi Liu;Yiling Lou

  • Approximate query service on autonomous IoT cameras

    Mengwei Xu;Xiwen Zhang;Yunxin Liu;Gang Huang

  • Generating synchronization engines between running systems and their model-based views

    Hui Song;Yingfei Xiong;Franck Chauvel;Gang Huang

  • iMashup: a mashup-based framework for service composition

    Xuan Zhe Liu;Gang Huang;Qi Zhao;Hong Mei

Frequent Co-Authors

Hong Mei
Hong Mei Peking University
Xuanzhe Liu
Xuanzhe Liu Peking University
Yingfei Xiong
Yingfei Xiong Peking University
Qiaozhu Mei
Qiaozhu Mei University of Michigan–Ann Arbor
Tao Xie
Tao Xie Peking University
Lu Zhang
Lu Zhang Peking University
Xiapu Luo
Xiapu Luo Hong Kong Polytechnic University
Zhenjiang Hu
Zhenjiang Hu Peking University
Xuxian Jiang
Xuxian Jiang PeckShield
Peter A. Dinda
Peter A. Dinda Northwestern University

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