World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
3854
World Ranking
13236
National Ranking
394

Kit Yan Chan 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 Kit Yan Chan 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: 184 publications — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Kit Yan Chan 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 Kit Yan Chan 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: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Overview

Kit Yan Chan is a researcher affiliated with Curtin University in Australia. Their work primarily spans the fields of Engineering and Computer Science, with a focus on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, and Signal Processing.

Their research covers various advanced technical topics including:

  • Advanced MIMO Systems Optimization
  • Cooperative Communication and Network Coding
  • Advanced Wireless Communication Technologies
  • Advanced Wireless Network Optimization
  • Energy Harvesting in Wireless Networks
  • Vehicular Ad Hoc Networks (VANETs)
  • Color perception and design

The researcher has published extensively in notable venues, including:

  • Computer Communications
  • Computer Networks
  • Sensors
  • IEEE Transactions on Vehicular Technology
  • IEEE Internet of Things Journal

Among recent papers authored or co-authored by Kit Yan Chan are:

  • Deep neural networks in the cloud: Review, applications, challenges and research directions (2023) published in Neurocomputing

Other relevant papers related to the broader research network include works in topics such as social influence prediction, energy-spectral efficiency optimization in vehicular communications, asset management for power transformers, and resource allocation in non-orthogonal multiple access networks, indicating intersecting research interests in communications and machine learning applications.

Frequent collaborators in their research endeavors include Yazhou Yuan, Zhixin Liu, Xinping Guan, and Yuan-ai Xie, with repeated joint publications, highlighting teamwork in advancing topics related to communication systems and optimization.

Best Publications

  • Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm

    Kit Yan Chan;T. S. Dillon;J. Singh;E. Chang

  • Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications

    S.H. Ling;H.H.C. Iu;K.Y. Chan;H.K. Lam

  • Improved Hybrid Particle Swarm Optimized Wavelet Neural Network for Modeling the Development of Fluid Dispensing for Electronic Packaging

    S.H. Ling;H. Iu;F.H.F. Leung;K.Y. Chan

  • Psychophysiology-Based QoE Assessment: A Survey

    Ulrich Engelke;Daniel P. Darcy;Grant H. Mulliken;Sebastian Bosse

  • Deep neural networks in the cloud: Review, applications, challenges and research directions

    Unknown

  • A methodology of generating customer satisfaction models for new product development using a neuro-fuzzy approach

    C. K. Kwong;T. C. Wong;K. Y. Chan

  • An Intelligent Particle Swarm Optimization for Short-Term Traffic Flow Forecasting Using on-Road Sensor Systems

    Kit Yan Chan;T. S. Dillon;E. Chang

  • An intelligent fuzzy regression approach for affective product design that captures nonlinearity and fuzziness

    Kit Yan Chan;C. Kwong;Tharam Dillon;K. Fung

  • Fuzzy logic control vs. conventional PID control of an inverted pendulum robot

    M.I.H. Nour;J. Ooi;K.Y. Chan

  • Diagnosis of hypoglycemic episodes using a neural network based rule discovery system

    K. Y. Chan;S. H. Ling;T. S. Dillon;H. T. Nguyen

  • Modeling of a Liquid Epoxy Molding Process Using a Particle Swarm Optimization-Based Fuzzy Regression Approach

    Kit Yan Chan;Tharam S Dillon;C K Kwong

  • Prediction of Short-Term Traffic Variables Using Intelligent Swarm-Based Neural Networks

    Kit Yan Chan;T. Dillon;E. Chang;J. Singh

  • Modeling manufacturing processes using a genetic programming-based fuzzy regression with detection of outliers

    K. Y. Chan;C. K. Kwong;T. C. Fogarty

  • CredSaT: Credibility ranking of users in big social data incorporating semantic analysis and temporal factor:

    Bilal Abu-Salih;Pornpit Wongthongtham;Kit Yan Chan;Dengya Zhu

  • A study of neural-network-based classifiers for material classification

    H. K. Lam;Udeme Ekong;Hongbin Liu;Bo Xiao

  • Twitter mining for ontology-based domain discovery incorporating machine learning

    Bilal Abu-Salih;Pornpit Wongthongtham;Kit Yan Chan

  • Reducing overfitting in manufacturing process modeling using a backward elimination based genetic programming

    K. Y. Chan;C. K. Kwong;T. S. Dillon;Y. C. Tsim

  • Selection of Significant On-Road Sensor Data for Short-Term Traffic Flow Forecasting Using the Taguchi Method

    Kit Yan Chan;S. Khadem;T. S. Dillon;V. Palade

  • Affective design using machine learning : a survey and its prospect of conjoining big data

    Kit Yan Chan;C.K. Kwong;Ponnie Clark;Huimin Jiang

  • Chance-Constrained Optimization in D2D-Based Vehicular Communication Network

    Zhixin Liu;Yuan'ai Xie;Kit Yan Chan;Kai Ma

  • Market segmentation and ideal point identification for new product design using fuzzy data compression and fuzzy clustering methods

    Kit Yan Chan;C. K. Kwong;B. Q. Hu

  • Time-aware domain-based social influence prediction

    Bilal Abu-Salih;Kit Yan Chan;Omar Sultan Al-Kadi;Marwan Al-Tawil

  • T–S Fuzzy-Model-Based Output Feedback Tracking Control With Control Input Saturation

    Yan Yu;Hak-Keung Lam;Kit Yan Chan

  • CredSaT: Credibility Ranking of Users in Big Social Data incorporating Semantic Analysis and Temporal Factor

    Bilal Abu-Salih;P. Wongthongtham;KY Chan;Z. Dengya

  • Rethinking prefabricated construction management using the VP-based IKEA model in Hong Kong

    Heng Li;Samuel H.L. Guo;Ronald Martin Skitmore;Ting Huang

Frequent Co-Authors

Tharam S. Dillon
Tharam S. Dillon La Trobe University
Sai Ho Ling
Sai Ho Ling University of Technology Sydney
Xinping Guan
Xinping Guan Shanghai Jiao Tong University
Terence C. Fogarty
Terence C. Fogarty London South Bank University
Sven Nordholm
Sven Nordholm Curtin University
Hak-Keung Lam
Hak-Keung Lam King's College London
Frank H. F. Leung
Frank H. F. Leung Hong Kong Polytechnic University
Herbert Ho-Ching Iu
Herbert Ho-Ching Iu University of Western Australia
Vasile Palade
Vasile Palade Coventry University
Elizabeth Chang
Elizabeth Chang Griffith University

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