World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
14961
World Ranking
3225
National Ranking
1566

Jian Tang 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 Jian Tang 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: 238 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Jian Tang 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 Jian Tang 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: 60 D-Index — 78th percentile

78% 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

  • 2019 - ACM Distinguished Member

Overview

Jian Tang is affiliated with Syracuse University in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence and related subfields.

Their research spans several specific areas within computer science, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Computer Networks and Communications
  • Control and Systems Engineering

They have worked on a variety of research topics, with notable focus on:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Graph Neural Networks
  • Computational Drug Discovery Methods
  • Machine Learning in Materials Science
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition

Jian Tang has published extensively in recognized venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Mobile Computing
  • IEEE Transactions on Network Science and Engineering

Recent notable papers include:

  • GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation, 2020, arXiv (Cornell University)
  • AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Robust Unsupervised Video Anomaly Detection by Multipath Frame Prediction, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Multi-modal molecule structure-text model for text-based retrieval and editing, 2023, Nature Machine Intelligence

Jian Tang has collaborated frequently with several coauthors, including:

  • Zhengping Che
  • Zhiyuan Xu
  • Yanzhi Wang
  • Shengchao Liu
  • Chi Harold Liu

Their work has been acknowledged by accolades such as the ACM Distinguished Member award in 2019.

Best Publications

  • Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing

    Dejun Yang;Guoliang Xue;Xi Fang;Jian Tang

  • Interference-aware topology control and QoS routing in multi-channel wireless mesh networks

    Jian Tang;Guoliang Xue;Weiyi Zhang

  • Energy-Efficient UAV Control for Effective and Fair Communication Coverage: A Deep Reinforcement Learning Approach

    Chi Harold Liu;Zheyu Chen;Jian Tang;Jie Xu

  • A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers

    Tianyun Zhang;Shaokai Ye;Kaiqi Zhang;Jian Tang

  • Relay node placement in large scale wireless sensor networks

    Jian Tang;Bin Hao;Arunabha Sen

  • Incentive mechanisms for crowdsensing: crowdsourcing with smartphones

    Dejun Yang;Guoliang Xue;Xi Fang;Jian Tang

  • Experience-driven Networking: A Deep Reinforcement Learning based Approach

    Zhiyuan Xu;Jian Tang;Jingsong Meng;Weiyi Zhang

  • Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach

    Jing Wang;Jian Tang;Zhiyuan Xu;Yanzhi Wang

  • Optimizing Electric Vehicle Charging: A Customer's Perspective

    Chenrui Jin;Jian Tang;Prasanta Ghosh

  • A Hierarchical Framework of Cloud Resource Allocation and Power Management Using Deep Reinforcement Learning

    Ning Liu;Zhe Li;Jielong Xu;Zhiyuan Xu

  • Optimizing Electric Vehicle Charging With Energy Storage in the Electricity Market

    Chenrui Jin;Jian Tang;P. Ghosh

  • A deep reinforcement learning based framework for power-efficient resource allocation in cloud RANs

    Zhiyuan Xu;Yanzhi Wang;Jian Tang;Jing Wang

  • Distributed Energy-Efficient Multi-UAV Navigation for Long-Term Communication Coverage by Deep Reinforcement Learning

    Chi Harold Liu;Xiaoxin Ma;Xudong Gao;Jian Tang

  • T-Storm: Traffic-Aware Online Scheduling in Storm

    Jielong Xu;Zhenhua Chen;Jian Tang;Sen Su

  • CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices

    Caiwen Ding;Siyu Liao;Yanzhi Wang;Zhe Li

  • Sensing as a Service: Challenges, Solutions and Future Directions

    Xiang Sheng;Jian Tang;Xuejie Xiao;Guoliang Xue

  • Constrained relay node placement in wireless sensor networks: formulation and approximations

    Satyajayant Misra;Seung Don Hong;Guoliang Xue;Jian Tang

  • Truthful incentive mechanisms for crowdsourcing

    Xiang Zhang;Guoliang Xue;Ruozhou Yu;Dejun Yang

  • Polynomial time approximation algorithms for multi-constrained QoS routing

    Guoliang Xue;Weiyi Zhang;Jian Tang;Krishnaiyan Thulasiraman

  • Energy-efficient collaborative sensing with mobile phones

    Xiang Sheng;Jian Tang;Weiyi Zhang

  • CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

    Caiwen Ding;Siyu Liao;Yanzhi Wang;Zhe Li

Frequent Co-Authors

Guoliang Xue
Guoliang Xue Arizona State University
Yanzhi Wang
Yanzhi Wang Northeastern University
Ninghua Zhu
Ninghua Zhu Chinese Academy of Sciences
Guangyu Zhang
Guangyu Zhang Chinese Academy of Sciences
Dejun Yang
Dejun Yang Colorado School of Mines
Yoshua Bengio
Yoshua Bengio University of Montreal
Qiaozhu Mei
Qiaozhu Mei University of Michigan–Ann Arbor
Chi Harold Liu
Chi Harold Liu Beijing Institute of Technology
Kenji Watanabe
Kenji Watanabe National Institute for Materials Science
Takashi Taniguchi
Takashi Taniguchi National Institute for Materials Science

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