World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
9239
World Ranking
4648
National Ranking
622

James Cheng 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 James Cheng 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: 173 publications — 36th percentile

36% of scientists in this discipline score the same or lower.

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

James Cheng 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 James Cheng 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: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Overview

James Cheng is affiliated with the Chinese University of Hong Kong in China. Their research focuses primarily on computer science with a significant contribution to the subfields of artificial intelligence, computer vision and pattern recognition, computer networks and communications, information systems, and statistical and nonlinear physics.

The main topics covered in their work include advanced graph neural networks, graph theory and algorithms, stochastic gradient optimization techniques, topic modeling, domain adaptation and few-shot learning, cloud computing and resource management, and recommender systems and techniques.

Cheng has published extensively, with frequent appearances in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Management of Data
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the VLDB Endowment
  • IEEE Transactions on Parallel and Distributed Systems

Selected recent papers include works such as:

  • ByteGNN, 2022, Proceedings of the VLDB Endowment
  • Measuring and Improving the Use of Graph Information in Graph Neural Networks, 2022, arXiv (Cornell University)
  • Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs, 2022, arXiv (Cornell University)
  • Rethinking Graph Regularization for Graph Neural Networks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Elastic Deep Learning in Multi-Tenant GPU Clusters, 2021, IEEE Transactions on Parallel and Distributed Systems

Frequent co-authors appearing alongside Cheng include:

  • Xiao Yan
  • Yongqiang Chen
  • Binghui Xie
  • Bo Han
  • Kaiwen Zhou

Best Publications

  • Truss decomposition in massive networks

    Jia Wang;James Cheng

  • K-isomorphism: privacy preserving network publication against structural attacks

    James Cheng;Ada Wai-chee Fu;Jia Liu

  • A model-based approach to attributed graph clustering

    Zhiqiang Xu;Yiping Ke;Yi Wang;Hong Cheng

  • Fg-index: towards verification-free query processing on graph databases

    James Cheng;Yiping Ke;Wilfred Ng;An Lu

  • Path problems in temporal graphs

    Huanhuan Wu;James Cheng;Silu Huang;Yiping Ke

  • Efficient core decomposition in massive networks

    James Cheng;Yiping Ke;Shumo Chu;M. Tamer Ozsu

  • Blogel: a block-centric framework for distributed computation on real-world graphs

    Da Yan;James Cheng;Yi Lu;Wilfred Ng

  • Large-scale distributed graph computing systems: an experimental evaluation

    Yi Lu;James Cheng;Da Yan;Huanhuan Wu

  • Triangle listing in massive networks and its applications

    Shumo Chu;James Cheng

  • Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications

    Fanhua Shang;James Cheng;Yuanyuan Liu;Zhi-Quan Luo

  • A survey on algorithms for mining frequent itemsets over data streams

    James Cheng;Yiping Ke;Wilfred Ng

  • Finding maximal cliques in massive networks

    James Cheng;Yiping Ke;Ada Wai-Chee Fu;Jeffrey Xu Yu

  • Fast algorithms for maximal clique enumeration with limited memory

    James Cheng;Linhong Zhu;Yiping Ke;Shumo Chu

  • Xqzip: Querying compressed XML using structural indexing

    James Cheng;Wilfred Ng

  • Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation

    Da Yan;James Cheng;Yi Lu;Wilfred Ng

  • Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data

    Yuanyuan Liu;Fanhua Shang;Licheng Jiao;James Cheng

  • Finding maximal cliques in massive networks by H*-graph

    James Cheng;Yiping Ke;Ada Wai-Chee Fu;Jeffrey Xu Yu

  • Efficient Algorithms for Temporal Path Computation

    Huanhuan Wu;James Cheng;Yiping Ke;Silu Huang

  • Pregel algorithms for graph connectivity problems with performance guarantees

    Da Yan;James Cheng;Kai Xing;Yi Lu

  • Reachability and time-based path queries in temporal graphs

    Huanhuan Wu;Yuzhen Huang;James Cheng;Jinfeng Li

  • Measuring and Improving the Use of Graph Information in Graph Neural Networks

    Yifan Hou;Jian Zhang;James Cheng;Kaili Ma

Frequent Co-Authors

Fanhua Shang
Fanhua Shang Tianjin University
Wilfred Ng
Wilfred Ng Hong Kong University of Science and Technology
Yiping Ke
Yiping Ke Chinese University of Hong Kong
Ada Wai-Chee Fu
Ada Wai-Chee Fu Chinese University of Hong Kong
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Licheng Jiao
Licheng Jiao Xidian University
John C. S. Lui
John C. S. Lui Chinese University of Hong Kong
M. Tamer Özsu
M. Tamer Özsu University of Waterloo
Zhou Zhao
Zhou Zhao Zhejiang University
Zhi-Quan Luo
Zhi-Quan Luo Chinese University of Hong Kong, Shenzhen

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