World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
9264
World Ranking
9143
National Ranking
116

Vincent W. Zheng 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 Vincent W. Zheng 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: 91 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Vincent W. Zheng 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 Vincent W. Zheng 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Vincent W. Zheng is affiliated with the Agency for Science, Technology and Research in Singapore. Their research spans the intersection of computer science and molecular biology, with particular emphasis on advanced computational methods and biological applications.

The scientist's main fields of study include:

  • Computer Science
  • Biochemistry, Genetics and Molecular Biology

Within these fields, their subfields of study focus on:

  • Artificial Intelligence
  • Molecular Biology
  • Statistical and Nonlinear Physics
  • Information Systems
  • Infectious Diseases

Vincent W. Zheng's research addresses a variety of topics, including:

  • Advanced Graph Neural Networks
  • Complex Network Analysis Techniques
  • Privacy-Preserving Technologies in Data
  • Recommender Systems and Techniques
  • Antimicrobial Resistance in Staphylococcus
  • Bacterial biofilms and quorum sensing
  • Bacterial Genetics and Biotechnology

Frequent publication venues for their work are:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers of Computer Science
  • IEEE Transactions on Learning Technologies
  • Nucleic Acids Research

Frequent co-authors who have collaborated with Vincent W. Zheng include:

  • Dane Parker
  • Jeffrey M. Boyd
  • Gustavo Rios-Delgado
  • Javiera Norambuena
  • Ronan K. Carroll

Representative recent papers authored or co-authored by Vincent W. Zheng are:

  • "Adam revisited: a weighted past gradients perspective," 2020, Frontiers of Computer Science
  • "CMKT: Concept Map Driven Knowledge Tracing," 2022, IEEE Transactions on Learning Technologies
  • "Neighbor-Anchoring Adversarial Graph Neural Networks," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "Accelerating Large-Scale Heterogeneous Interaction Graph Embedding Learning via Importance Sampling," 2020, ACM Transactions on Knowledge Discovery from Data
  • "Privacy Threats Against Federated Matrix Factorization," 2020, arXiv (Cornell University)

Best Publications

  • A Comprehensive Survey of Graph Embedding: Problems, Techniques, and Applications

    Hongyun Cai;Vincent W. Zheng;Kevin Chen-Chuan Chang

  • Collaborative location and activity recommendations with GPS history data

    Vincent W. Zheng;Yu Zheng;Xing Xie;Qiang Yang

  • Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs

    Dingqi Yang;Daqing Zhang;Vincent W. Zheng;Zhiyong Yu

  • A Survey of Zero-Shot Learning: Settings, Methods, and Applications

    Wei Wang;Vincent W. Zheng;Han Yu;Chunyan Miao

  • Collaborative filtering meets mobile recommendation: a user-centered approach

    Vincent W. Zheng;Bin Cao;Yu Zheng;Xing Xie

  • Learning Community Embedding with Community Detection and Node Embedding on Graphs

    Sandro Cavallari;Vincent W. Zheng;Hongyun Cai;Kevin Chen-Chuan Chang

  • Towards mobile intelligence: Learning from GPS history data for collaborative recommendation

    Vincent W. Zheng;Yu Zheng;Xing Xie;Qiang Yang

  • KnowEdu: A System to Construct Knowledge Graph for Education

    Penghe Chen;Yu Lu;Vincent W. Zheng;Xiyang Chen

  • Topological Recurrent Neural Network for Diffusion Prediction

    Jia Wang;Vincent W. Zheng;Zemin Liu;Kevin Chen-Chuan Chang

  • Federated Recommendation Systems.

    Liu Yang;Ben Tan;Vincent W. Zheng;Kai Chen

  • Prerequisite-Driven Deep Knowledge Tracing

    Penghe Chen;Yu Lu;Vincent W. Zheng;Yang Pian

  • Estimating Location Using Wi-Fi

    Qiang Yang;Sinno Jialin Pan;Vincent Wenchen Zheng

  • Differentially Private Federated Knowledge Graphs Embedding

    Hao Peng;Haoran Li;Yangqiu Song;Vincent Zheng

  • Deep Transfer Learning for Cross-domain Activity Recognition

    Jindong Wang;Vincent W. Zheng;Yiqiang Chen;Meiyu Huang

  • Cross-domain activity recognition

    Vincent Wenchen Zheng;Derek Hao Hu;Qiang Yang

  • Transferring multi-device localization models using latent multi-task learning

    Vincent Wenchen Zheng;Sinno Jialin Pan;Qiang Yang;Jeffrey Junfeng Pan

  • Semantic proximity search on graphs with metagraph-based learning

    Yuan Fang;Wenqing Lin;Vincent W. Zheng;Min Wu

  • Abnormal activity recognition based on HDP-HMM models

    Derek Hao Hu;Xian-Xing Zhang;Jie Yin;Vincent Wenchen Zheng

  • Real world activity recognition with multiple goals

    Derek Hao Hu;Sinno Jialin Pan;Vincent Wenchen Zheng;Nathan Nan Liu

  • Cross-domain activity recognition via transfer learning

    Derek Hao Hu;Vincent Wenchen Zheng;Qiang Yang

  • CEPR: A Collaborative Exploration and Periodically Returning Model for Location Prediction

    Defu Lian;Xing Xie;Vincent W. Zheng;Nicholas Jing Yuan

Frequent Co-Authors

Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Kevin Chen-Chuan Chang
Kevin Chen-Chuan Chang University of Illinois at Urbana-Champaign
Yangqiu Song
Yangqiu Song Hong Kong University of Science and Technology
Enhong Chen
Enhong Chen University of Science and Technology of China
Zhou Zhao
Zhou Zhao Zhejiang University
Yu Zheng
Yu Zheng Jingdong (China)
Erik Cambria
Erik Cambria Nanyang Technological University
Sinno Jialin Pan
Sinno Jialin Pan Chinese University of Hong Kong
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Xing Xie
Xing Xie Microsoft Research Asia (China)

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to various online degrees and career options. Many students also consider related fields, such as physics, data science, and electrical engineering. Affordable and flexible programs make it easier to expand your skills while managing your schedule.

For those interested in physical sciences, online physics degrees provide rigorous training with the convenience of remote study. If you’re looking for a data-driven career, the cheapest data science degree programs help you gain in-demand analytics skills at a lower cost.

Engineering-minded students may pursue an online master’s in electrical engineering degree to unlock technical and leadership roles. Additionally, those seeking quick entry into the tech workforce can consider easy certifications to get that offer strong earning potential.

Each pathway supports a range of professional goals, allowing you to tailor your education and advance your career in science and technology.

Best Scientists Citing Vincent W. Zheng

Trending Scientists

Recently Published Articles