World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
38
Citations
4765
World Ranking
8169
National Ranking
99

Kang Tai publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Kang Tai sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 150 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Kang Tai D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Kang Tai sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 38 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Kang Tai is affiliated with Nanyang Technological University in Singapore and has produced research primarily in the fields of Engineering and Physics and Astronomy. Their scholarly output spans a diverse range of topics and subfields, reflecting a multidisciplinary approach to scientific and technical challenges.

The prominent subfields Kang Tai has contributed to include Automotive Engineering, Atomic and Molecular Physics and Optics, Control and Systems Engineering, Electrical and Electronic Engineering, and Statistical and Nonlinear Physics.

The main topics covered in their research portfolio are:

  • Advanced Battery Technologies Research
  • Electric and Hybrid Vehicle Technologies
  • Piezoelectric Actuators and Control
  • Force Microscopy Techniques and Applications
  • Maritime Transport Emissions and Efficiency
  • Advanced MEMS and NEMS Technologies
  • Advanced Thermodynamics and Statistical Mechanics

Kang Tai has published a number of recent papers, with a focus on both theoretical and applied aspects of engineering and transport systems. Selected recent publications are listed below:

  • "A comprehensive numerical study based on topology optimization for cooling plates thermal design of battery packs," 2023, Applied Thermal Engineering
  • "Optimal Power and Energy Management Control for Hybrid Fuel Cell-Fed Shipboard DC Microgrid," 2023, IEEE Transactions on Intelligent Transportation Systems
  • "DC-Distributed Power System Modeling and Hardware-in-the-Loop (HIL) Evaluation of Fuel Cell-Powered Marine Vessel," 2021, IEEE Journal of Emerging and Selected Topics in Industrial Electronics
  • "Topological network and GIS approach to modeling earthquake risk of infrastructure systems: A case study in Japan," 2021, Applied Geography
  • "Design of a two-stage compliant asymmetric piezoelectrically actuated microgripper with parasitic motion compensation," 2023, Mechanical Systems and Signal Processing

The frequent co-authors working with Kang Tai include Wenjie Chen, Ahmed Abdelhakim, Huifeng Tan, M.W.S. Lau, and Ricky R. Chan. These collaborators have contributed to multiple studies across various engineering and technological topics.

Kang Tai's publications often appear in journals with a focus on applied engineering and technology. Venues where Kang Tai has frequently published include:

  • Energy
  • Sensors and Actuators A Physical
  • Advances in Space Research
  • SSRN Electronic Journal
  • Applied Thermal Engineering

Best Publications

  • MULTIOBJECTIVE DESIGN OPTIMIZATION BY AN EVOLUTIONARY ALGORITHM

    Tapabrata Ray;Kang Tai;Kin Chye Seow

  • Structural topology design optimization using Genetic Algorithms with a bit-array representation

    S.Y. Wang;S.Y. Wang;K. Tai;K. Tai

  • A SOCIO-BEHAVIOURAL SIMULATION MODEL FOR ENGINEERING DESIGN OPTIMIZATION

    Shamim Akhtar;Kang Tai;Tapabrata Ray

  • Comparison of statistical and machine learning methods in modelling of data with multicollinearity

    Akhil Garg;Kang Tai

  • An enhanced genetic algorithm for structural topology optimization

    Shengyin Wang;Kang Tai;Michael Yu Wang

  • State-of-the-art in empirical modelling of rapid prototyping processes

    A. Garg;K. Tai;M.M. Savalani

  • An evolutionary approach for cooling system optimization in plastic injection moulding

    Y. C. Lam;L. Y. Zhai;K. Tai;S. C. Fok

  • Design of structures and compliant mechanisms by evolutionary optimization of morphological representations of topology

    K. Tai;T. H. Chee

  • Design Synthesis of Path Generating Compliant Mechanisms by Evolutionary Optimization of Topology and Shape

    Kang Tai;Guang Yu Cui;Tapabrata Ray

  • Graph representation for structural topology optimization using genetic algorithms

    S.Y. Wang;S.Y. Wang;K. Tai;K. Tai

  • Probability Collectives: A multi-agent approach for solving combinatorial optimization problems

    Anand J. Kulkarni;K. Tai

  • An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes

    Akhil Garg;Ankit Garg;K. Tai;S. Sreedeep

  • Performance evaluation of microbial fuel cell by artificial intelligence methods

    A. Garg;V. Vijayaraghavan;S. S. Mahapatra;K. Tai

  • Radial point interpolation collocation method (RPICM) for partial differential equations

    X. Liu;G. R. Liu;K. Tai;K. Y. Lam

  • Analytical gradient-based optimization of offshore wind turbine substructures under fatigue and extreme loads

    Kok Hon Chew;Kok Hon Chew;Kang Tai;E.Y.K. Ng;Michael Muskulus

  • A multi-gene genetic programming model for estimating stress-dependent soil water retention curves

    Akhil Garg;Ankit Garg;K. Tai

  • Topology optimization of piezoelectric sensors/actuators for torsional vibration control of composite plates

    S Y Wang;K Tai;S T Quek

  • Structural topology optimization using a genetic algorithm with a morphological geometric representation scheme

    K. Tai;S. Akhtar

  • Network topological approach to modeling accident causations and characteristics: analysis of railway incidents in Japan

    Chi Yung Lam;Kang Tai

  • Review of genetic programming in modeling of machining processes

    A. Garg;K. Tai

Frequent Co-Authors

Akhil Garg
Akhil Garg Huazhong University of Science and Technology
Chee How Wong
Chee How Wong Nanyang Technological University
Ajith Abraham
Ajith Abraham Sai University
Liang Gao
Liang Gao Huazhong University of Science and Technology
Gui-Rong Liu
Gui-Rong Liu University of Cincinnati
Eddie Y. K. Ng
Eddie Y. K. Ng Nanyang Technological University
Siba Sankar Mahapatra
Siba Sankar Mahapatra National Institute of Technology Rourkela
Tapabrata Ray
Tapabrata Ray University of New South Wales
Robert L. K. Tiong
Robert L. K. Tiong Nanyang Technological University
Ning Wang
Ning Wang Dalian Maritime University

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