World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
6223
World Ranking
6277
National Ranking
57

R. J. Kuo 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 R. J. Kuo 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: 108 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

R. J. Kuo 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 R. J. Kuo 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: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Overview

R. J. Kuo is affiliated with the National Taiwan University of Science and Technology in Taiwan and has contributed extensively to the fields of Computer Science and Engineering. Their research spans a range of specialized subfields, particularly focusing on Artificial Intelligence, Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Information Systems, and Marketing.

Their work addresses several core topics including Advanced Clustering Algorithms Research, Vehicle Routing Optimization Methods, Metaheuristic Optimization Algorithms Research, Recommender Systems and Techniques, Multi-Criteria Decision Making, UAV Applications and Optimization, and Digital Marketing and Social Media.

Recent papers authored by R. J. Kuo include:

  • "Vehicle routing problem with drones considering time windows" (2021) published in Expert Systems with Applications
  • "Applying particle swarm optimization algorithm-based collaborative filtering recommender system considering rating and review" (2023) published in Applied Soft Computing
  • "Application of improved multi-objective particle swarm optimization algorithm to solve disruption for the two-stage vehicle routing problem with time windows" (2023) published in Expert Systems with Applications
  • "Applying NSGA-II to vehicle routing problem with drones considering makespan and carbon emission" (2023) published in Expert Systems with Applications

R. J. Kuo has frequently published in venues such as Applied Soft Computing, Expert Systems with Applications, Soft Computing, Computers & Industrial Engineering, and Information Sciences.

Collaborative work is a significant element of their research activity. Frequent co-authors include Thi Phuong Quyen Nguyen, Ferani E. Zulvia, Shih-Hao Lu, Setyo Tri Windras Mara, and Maya Cendana.

Best Publications

  • Integration of self-organizing feature map and K-means algorithm for market segmentation

    R. J. Kuo;L. M. Ho;C. M. Hu

  • Application of particle swarm optimization to association rule mining

    R. J. Kuo;C. M. Chao;Y. T. Chiu

  • A hybrid of genetic algorithm and particle swarm optimization for solving bi-level linear programming problem – A case study on supply chain model

    R.J. Kuo;Y.S. Han

  • A sales forecasting system based on fuzzy neural network with initial weights generated by genetic algorithm

    Unknown

  • Integration of particle swarm optimization-based fuzzy neural network and artificial neural network for supplier selection

    R.J. Kuo;S.Y. Hong;Y.C. Huang

  • Application of ant K-means on clustering analysis

    R. J. Kuo;H. S. Wang;Tung-Lai Hu;S. H. Chou

  • A many-objective gradient evolution algorithm for solving a green vehicle routing problem with time windows and time dependency for perishable products

    Unknown

  • Application of particle swarm optimization algorithm for solving bi-level linear programming problem

    R. J. Kuo;C. C. Huang

  • Vehicle Routing Problem with Drones Considering Time Windows

    R.J. Kuo;Shih-Hao Lu;Pei-Yu Lai;Setyo Tri Windras Mara

  • Integration of particle swarm optimization and genetic algorithm for dynamic clustering

    Unknown

  • A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights

    R. J. Kuo;K. C. Xue

  • Location-routing problem: a classification of recent research

    Unknown

  • An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination

    R. J. Kuo;P. Wu;C. P. Wang

  • Application of a hybrid of genetic algorithm and particle swarm optimization algorithm for order clustering

    R. J. Kuo;L. M. Lin

  • Hybrid particle swarm optimization with genetic algorithm for solving capacitated vehicle routing problem with fuzzy demand - A case study on garbage collection system

    Unknown

  • Integration of self-organizing feature maps neural network and genetic K-means algorithm for market segmentation

    R. J. Kuo;Y. L. An;H. S. Wang;W. J. Chung

  • Multi-sensor integration for on-line tool wear estimation through radial basis function networks and fuzzy neural network

    R. J. Kuo;P. H. Cohen

  • A decision support system for order selection in electronic commerce based on fuzzy neural network supported by real-coded genetic algorithm

    Ren Jie Kuo;J. A. Chen

  • Integration of ART2 neural network and genetic K-means algorithm for analyzing web browsing paths in electronic commerce

    R. J. Kuo;J. L. Liao;C. Tu

  • Mining association rules through integration of clustering analysis and ant colony system for health insurance database in Taiwan

    R. J. Kuo;S. Y. Lin;C. W. Shih

  • Association rule mining through the ant colony system for National Health Insurance Research Database in Taiwan

    R. J. Kuo;C. W. Shih

  • Cluster analysis in industrial market segmentation through artificial neural network

    R. J. Kuo;L. M. Ho;C. M. Hu

  • Simulation optimization using particle swarm optimization algorithm with application to assembly line design

    R. J. Kuo;C. Y. Yang

  • Developing a diagnostic system through integration of fuzzy case-based reasoning and fuzzy ant colony system

    R. J. Kuo;Y. P. Kuo;Kai-Ying Chen

  • Integration of Self-Organizing Feature Maps and Genetic-Algorithm-Based Clustering Method for Market Segmentation

    R. J. Kuo;K. Chang;S. Y. Chien

  • An application of a metaheuristic algorithm-based clustering ensemble method to APP customer segmentation

    R.J. Kuo;C.H. Mei;F.E. Zulvia;C.Y. Tsai

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