World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
11291
World Ranking
5065
National Ranking
686

Reynold 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 Reynold 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: 219 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Reynold 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 Reynold 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: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Overview

Reynold Cheng is affiliated with the University of Hong Kong in China and has conducted extensive research primarily in the fields of Computer Science and Engineering. Their work is largely focused on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Transportation, Building and Construction, and Information Systems.

Their research topics cover a range of specialized areas including:

  • Advanced Graph Neural Networks
  • Traffic Prediction and Management Techniques
  • Complex Network Analysis Techniques
  • Data Management and Algorithms
  • Graph Theory and Algorithms
  • Human Mobility and Location-Based Analysis
  • COVID-19 epidemiological studies

Reynold Cheng has published in several venues, with frequent publications in:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • IEEE Transactions on Knowledge and Data Engineering
  • SSRN Electronic Journal
  • Advanced Therapeutics

Among their recent papers are:

  • Changes in local travel behaviour before and during the COVID-19 pandemic in Hong Kong (2021), published in Cities
  • Effects of Human Behavior Changes During the Coronavirus Disease 2019 (COVID-19) Pandemic on Influenza Spread in Hong Kong (2020), published in Clinical Infectious Diseases
  • Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs (2023), published in arXiv (Cornell University)
  • Graphix-T5: Mixing Pre-trained Transformers with Graph-Aware Layers for Text-to-SQL Parsing (2023), published in Proceedings of the AAAI Conference on Artificial Intelligence
  • DeepTEA (2022), published in Proceedings of the VLDB Endowment

Reynold Cheng has collaborated frequently with co-authors including Chenhao Ma, Laks V. S. Lakshmanan, Jinyang Li, Bowen Qin, and Nan Huo. The volume of these collaborations highlights sustained joint research efforts over multiple projects.

Best Publications

  • Evaluating probabilistic queries over imprecise data

    Reynold Cheng;Dmitri V. Kalashnikov;Sunil Prabhakar

  • Querying imprecise data in moving object environments

    R. Cheng;D.V. Kalashnikov;S. Prabhakar

  • Truth inference in crowdsourcing: is the problem solved?

    Yudian Zheng;Guoliang Li;Yuanbing Li;Caihua Shan

  • Preserving user location privacy in mobile data management infrastructures

    Reynold Cheng;Yu Zhang;Elisa Bertino;Sunil Prabhakar

  • Indexing multi-dimensional uncertain data with arbitrary probability density functions

    Yufei Tao;Reynold Cheng;Xiaokui Xiao;Wang Kay Ngai

  • Efficient indexing methods for probabilistic threshold queries over uncertain data

    Reynold Cheng;Yuni Xia;Sunil Prabhakar;Rahul Shah

  • Efficient Clustering of Uncertain Data

    Wang Ngai;Ben Kao;Chun Chui;Reynold Cheng

  • Effective community search for large attributed graphs

    Yixiang Fang;Reynold Cheng;Siqiang Luo;Jiafeng Hu

  • A survey of community search over big graphs

    Yixiang Fang;Xin Huang;Lu Qin;Ying Zhang

  • Uncertain data mining: an example in clustering location data

    Michael Chau;Reynold Cheng;Ben Kao;Jackey Ng

  • Naive Bayes Classification of Uncertain Data

    Jiangtao Ren;Sau Dan Lee;Xianlu Chen;Ben Kao

  • QASCA: A Quality-Aware Task Assignment System for Crowdsourcing Applications

    Yudian Zheng;Jiannan Wang;Guoliang Li;Reynold Cheng

  • Range search on multidimensional uncertain data

    Yufei Tao;Xiaokui Xiao;Reynold Cheng

  • Meta Structure: Computing Relevance in Large Heterogeneous Information Networks

    Zhipeng Huang;Yudian Zheng;Reynold Cheng;Yizhou Sun

  • Effective community search over large spatial graphs

    Yixiang Fang;Reynold Cheng;Xiaodong Li;Siqiang Luo

  • Probabilistic Verifiers: Evaluating Constrained Nearest-Neighbor Queries over Uncertain Data

    R. Cheng;Jinchuan Chen;M. Mokbel;Chi-Yin Chow

  • Mining uncertain data with probabilistic guarantees

    Liwen Sun;Reynold Cheng;David W. Cheung;Jiefeng Cheng

  • Online Influence Maximization

    Siyu Lei;Silviu Maniu;Luyi Mo;Reynold Cheng

  • Efficient Evaluation of Imprecise Location-Dependent Queries

    Jinchuan Chen;R. Cheng

  • On querying historical evolving graph sequences

    Chenghui Ren;Eric Lo;Ben Kao;Xinjie Zhu

Frequent Co-Authors

Ben Kao
Ben Kao University of Hong Kong
Sunil Prabhakar
Sunil Prabhakar Purdue University West Lafayette
Nikos Mamoulis
Nikos Mamoulis University of Ioannina
David W. Cheung
David W. Cheung University of Hong Kong
Man Lung Yiu
Man Lung Yiu Hong Kong Polytechnic University
Xuemin Lin
Xuemin Lin Shanghai Jiao Tong University
Michael Chau
Michael Chau University of Hong Kong
Elisa Bertino
Elisa Bertino Purdue University West Lafayette
Yuguo Li
Yuguo Li University of Hong Kong
Wenjie Zhang
Wenjie Zhang University of New South Wales

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