World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4553
World Ranking
14004
National Ranking
5565

Wei-Shinn Ku 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 Wei-Shinn Ku 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 200 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Wei-Shinn Ku 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 Wei-Shinn Ku sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Wei-Shinn Ku is affiliated with Auburn University in the United States. Their research output spans several areas within computer science and engineering, focusing prominently on artificial intelligence, computer networks and communications, and transportation.

The primary fields of study for Wei-Shinn Ku include:

  • Computer Science
  • Engineering

Key subfields of study cover:

  • Artificial Intelligence
  • Computer Networks and Communications
  • Transportation
  • Computer Vision and Pattern Recognition
  • Molecular Biology

The scientist's work addresses a variety of topics such as:

  • Human Mobility and Location-Based Analysis
  • Traffic Prediction and Management Techniques
  • Advanced Graph Neural Networks
  • Cryptography and Data Security
  • Privacy-Preserving Technologies in Data
  • Data Management and Algorithms
  • Opportunistic and Delay-Tolerant Networks

Wei-Shinn Ku has contributed papers to several publication venues, with multiple articles appearing in the following outlets:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • 2022 IEEE International Conference on Big Data (Big Data)
  • IEEE Transactions on Network Science and Engineering
  • 2022 IEEE 38th International Conference on Data Engineering (ICDE)

Notable recent papers include:

  • "Freeway Travel Time Prediction Using Deep Hybrid Model - Taking Sun Yat-Sen Freeway as an Example," 2020, IEEE Transactions on Vehicular Technology
  • "G-thinker: a general distributed framework for finding qualified subgraphs in a big graph with load balancing," 2021, The VLDB Journal
  • "Privacy-Preserving Collaborative Filtering Using Fully Homomorphic Encryption," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "An RFID Zero-Knowledge Authentication Protocol Based on Quadratic Residues," 2021, IEEE Internet of Things Journal
  • "Towards Wireless Power Transfer in Mobile Social Networks," 2021, IEEE Transactions on Network Science and Engineering

Wei-Shinn Ku has frequently co-authored with several researchers, including:

  • Min-Te Sun
  • Kazuya Sakai
  • Bo Hui
  • Da Yan
  • Po-Wei Harn

Best Publications

  • Advances in Spatial and Temporal Databases

    Michael Gertz;Matthias Renz;Xiaofang Zhou;Erik Hoel

  • Collaborative Detection of DDoS Attacks over Multiple Network Domains

    Yu Chen;Kai Hwang;Wei-Shinn Ku

  • Strike (With) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects

    Michael A. Alcorn;Qi Li;Zhitao Gong;Chengfei Wang

  • Malicious node detection in wireless sensor networks using weighted trust evaluation

    Idris M. Atakli;Hongbing Hu;Yu Chen;Wei Shinn Ku

  • Distributed continuous range query processing on moving objects

    Haojun Wang;Roger Zimmermann;Wei-Shinn Ku

  • Leveraging spatio-temporal redundancy for RFID data cleansing

    Haiquan Chen;Wei-Shinn Ku;Haixun Wang;Min-Te Sun

  • The multi-rule partial sequenced route query

    Haiquan Chen;Wei-Shinn Ku;Min-Te Sun;Roger Zimmermann

  • Spatial Query Integrity with Voronoi Neighbors

    Ling Hu;Wei-Shinn Ku;S. Bakiras;C. Shahabi

  • Location-Based Spatial Query Processing with Data Sharing in Wireless Broadcast Environments

    Wei-Shinn Ku;Roger Zimmermann;Haixun Wang

  • Efficient Evaluation of k-Range Nearest Neighbor Queries in Road Networks

    Jie Bao;Chi-Yin Chow;Mohamed F. Mokbel;Wei-Shinn Ku

  • Query Integrity Assurance of Location-Based Services Accessing Outsourced Spatial Databases

    Wei-Shinn Ku;Ling Hu;Cyrus Shahabi;Haixun Wang

  • Analysis of Integrity Vulnerabilities and a Non-repudiation Protocol for Cloud Data Storage Platforms

    Jun Feng;Yu Chen;Wei-Shinn Ku;Pu Liu

  • Privacy Protected Query Processing on Spatial Networks

    Wei-Shinn Ku;R. Zimmermann;Wen-Chih Peng;S. Shroff

  • A Cloaking Algorithm Based on Spatial Networks for Location Privacy

    Po-YiLi;Wen-Chih Peng;Tsung-Wei Wang;Wei-Shinn Ku

  • Privacy Protected Spatial Query Processing for Advanced Location Based Services

    Wei-Shinn Ku;Yu Chen;Roger Zimmermann

  • Adaptive nearest neighbor queries in travel time networks

    Wei-Shinn Ku;Roger Zimmermann;Haojun Wang;Chi-Ngai Wan

  • Efficient Parallel Skyline Evaluation Using MapReduce

    Ji Zhang;Xunfei Jiang;Wei-Shinn Ku;Xiao Qin

  • G-thinker: A Distributed Framework for Mining Subgraphs in a Big Graph

    Da Yan;Guimu Guo;Mashiur Rahman Chowdhury;M. Tamer Ozsu

  • Freeway Travel Time Prediction Using Deep Hybrid Model – Taking Sun Yat-Sen Freeway as an Example

    Pei-Ya Ting;Tomotaka Wada;Yi-Lun Chiu;Min-Te Sun

  • Enhancing cloud storage security against roll-back attacks with a new fair multi-party non-repudiation protocol

    Jun Feng;Yu Chen;Douglas Summerville;Wei-Shinn Ku

  • Learning-Based Cleansing for Indoor RFID Data

    Asif Iqbal Baba;Manfred Jaeger;Hua Lu;Torben Bach Pedersen

  • An RFID and particle filter-based indoor spatial query evaluation system

    Jiao Yu;Wei-Shinn Ku;Min-Te Sun;Hua Lu

  • Weighted trust evaluation-based malicious node detection for wireless sensor networks

    Hongbing Hu;Yu Chen;Wei-Shinn Ku;Zhou Su

Frequent Co-Authors

Roger Zimmermann
Roger Zimmermann National University of Singapore
Yu Chen
Yu Chen Binghamton University
Xiao Qin
Xiao Qin Auburn University
Haixun Wang
Haixun Wang Instacart
Hua Lu
Hua Lu Aalborg University
Cyrus Shahabi
Cyrus Shahabi University of Southern California
Jie Wu
Jie Wu Temple University
Kai Hwang
Kai Hwang Chinese University of Hong Kong, Shenzhen
Torben Bach Pedersen
Torben Bach Pedersen Aalborg University
Wen-Chih Peng
Wen-Chih Peng National Yang Ming Chiao Tung University

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

If you're considering a Computer Science degree in the USA, you may also be interested in exploring related online degrees that open up diverse career opportunities. For those looking for options with great earning potential, there are several high-paying jobs with environmental science degree backgrounds—especially in emerging green technology roles that overlap with computing.

Students seeking a fast track can choose from an array of accelerated cs degree programs online, helping them launch their tech careers sooner. Additionally, engineering fields such as environmental and mechanical engineering have increasingly accessible online options. The environmental engineering online degree pathway is ideal for students with an interest in sustainability and technology.

For those concerned about tuition costs, it’s worth researching the mechanical engineering degree cost at accredited online institutions, which can make this in-demand STEM field more affordable. No matter your interests, a clear understanding of these pathways can lead to a successful tech-oriented career.

Best Scientists Citing Wei-Shinn Ku

Trending Scientists

Recently Published Articles