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Computer Science
China
2026

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 93 524 508 72 70 590 31198

Kay Chen Tan publications per year

The chart shows the history of publications by Kay Chen Tan between 1982 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Kay Chen Tan published across 44 years, from 1982 to 2025, averaging 18.1 papers a year. Output peaked at 74 publications in 2024. 133 of the 797 publications appeared in the last two years.

No. of publications
20 40 60
Bar chart. Horizontal axis: year, 1982 to 2025. Vertical axis: number of publications, 0 to 74. Peak 74 publications in 2024. 1982: 1 publication 1983: 0 publications 1984: 0 publications 1985: 0 publications 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 1 publication 1993: 0 publications 1994: 0 publications 1995: 2 publications 1996: 3 publications 1997: 7 publications 1998: 2 publications 1999: 3 publications 2000: 15 publications 2001: 15 publications 2002: 15 publications 2003: 17 publications 2004: 14 publications 2005: 25 publications 2006: 33 publications 2007: 39 publications 2008: 21 publications 2009: 30 publications 2010: 20 publications 2011: 12 publications 2012: 16 publications 2013: 28 publications 2014: 16 publications 2015: 19 publications 2016: 26 publications 2017: 26 publications 2018: 23 publications 2019: 28 publications 2020: 32 publications 2021: 71 publications 2022: 57 publications 2023: 47 publications 2024: 74 publications 2025: 59 publications
1982 2025

797 publications in total across all disciplines

View publications per year as a table
Kay Chen Tan: publications per year, 1982 to 2025
Year Publications
1982 1
1983 0
1984 0
1985 0
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 1
1993 0
1994 0
1995 2
1996 3
1997 7
1998 2
1999 3
2000 15
2001 15
2002 15
2003 17
2004 14
2005 25
2006 33
2007 39
2008 21
2009 30
2010 20
2011 12
2012 16
2013 28
2014 16
2015 19
2016 26
2017 26
2018 23
2019 28
2020 32
2021 71
2022 57
2023 47
2024 74
2025 59
Total 797
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Kay Chen Tan 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 Kay Chen Tan sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 582–591 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 590 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33 590
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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Kay Chen Tan 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 Kay Chen Tan sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 92–93 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 93 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57 93
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Research.com Recognitions

  • 2026 - Research.com Computer Science in China Leader Award
  • 2025 - Research.com Computer Science in China Leader Award
  • 2014 - IEEE Fellow For contributions to evolutionary multiobjective optimization

Overview

Kay Chen Tan is affiliated with the Hong Kong Polytechnic University in China. Their research primarily focuses on computer science, with substantial contributions to the subfields of artificial intelligence, computational theory and mathematics, electrical and electronic engineering, cognitive neuroscience, and computer vision and pattern recognition.

The scientist's main topics of work include advanced multi-objective optimization algorithms, metaheuristic optimization algorithms research, evolutionary algorithms and applications, advanced memory and neural computing, neural dynamics and brain function, neural networks and reservoir computing, and machine learning and data classification.

Among recent publications, notable papers include:

  • A survey on evolutionary computation for complex continuous optimization, 2021, Artificial Intelligence Review
  • Evolutionary Large-Scale Multi-Objective Optimization: A Survey, 2021, ACM Computing Surveys
  • A Survey on Evolutionary Constrained Multiobjective Optimization, 2022, IEEE Transactions on Evolutionary Computation
  • Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multiobjective Optimization, 2021, IEEE Transactions on Cybernetics
  • Solving Large-Scale Multiobjective Optimization Problems With Sparse Optimal Solutions via Unsupervised Neural Networks, 2020, IEEE Transactions on Cybernetics

Frequent co-authors in their research include Liang Feng, Jibin Wu, Qiuzhen Lin, Yaochu Jin, and Min Jiang.

The scientist has published extensively in venues such as arXiv (Cornell University), IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Computational Intelligence Magazine.

They have also contributed to book publications, notably with Springer Nature, including the book Evolutionary Multi-Task Optimization published in 2023.

Kay Chen Tan was awarded the IEEE Fellow distinction in 2014 for contributions to evolutionary multiobjective optimization.

Best Publications

  • Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics

    Chong Zhang;Pin Lim;A. K. Qin;Kay Chen Tan

  • A Competitive-Cooperative Coevolutionary Paradigm for Dynamic Multiobjective Optimization

    Chi-Keong Goh;Kay Chen Tan

  • A Multi-Facet Survey on Memetic Computation

    Xianshun Chen;Yew-Soon Ong;Meng-Hiot Lim;Kay Chen Tan

  • Heuristic methods for vehicle routing problem with time windows

    K.C Tan;L.H Lee;Q.L Zhu;K Ou

  • A Generic Deep-Learning-Based Approach for Automated Surface Inspection

    Ruoxu Ren;Terence Hung;Kay Chen Tan

  • Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons

    K. C. Tan;T. H. Lee;E. F. Khor

  • Evolutionary artificial potential fields and their application in real time robot path planning

    P. Vadakkepat;Kay Chen Tan;Wang Ming-Liang

  • A Survey on Evolutionary Neural Architecture Search.

    Yuqiao Liu;Yanan Sun;Bing Xue;Mengjie Zhang

  • Multiobjective Multifactorial Optimization in Evolutionary Multitasking

    Abhishek Gupta;Yew-Soon Ong;Liang Feng;Kay Chen Tan

  • Multiobjective Evolutionary Algorithms and Applications

    Kay Chen Tan;Tong Heng Lee;k-c-tan;Eik Fun Khor

  • Evolutionary Multitasking via Explicit Autoencoding

    Liang Feng;Lei Zhou;Jinghui Zhong;Abhishek Gupta

  • A survey on evolutionary computation for complex continuous optimization

    Zhi-Hui Zhan;Lin Shi;Kay Chen Tan;Jun Zhang;Jun Zhang

  • Evolutionary Large-Scale Multi-Objective Optimization: A Survey

    Ye Tian;Langchun Si;Xingyi Zhang;Ran Cheng

  • Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization

    K.C. Tan;T.H. Lee;E.F. Khor

  • Balancing Objective Optimization and Constraint Satisfaction in Constrained Evolutionary Multiobjective Optimization.

    Ye Tian;Yajie Zhang;Yansen Su;Xingyi Zhang

  • 2015 IEEE Symposium Series on Computational Intelligence

    Honorary Chairs;Jacek Zurada;Andries Engelbrecht;Mengjie Zhang

  • A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization

    Dasheng Liu;K.C. Tan;C.K. Goh;W.K. Ho

  • A distributed Cooperative coevolutionary algorithm for multiobjective optimization

    K.C. Tan;Y.J. Yang;C.K. Goh

  • A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design

    Chi Keong Goh;Kay Chen Tan;D. S. Liu;Swee Chiang Chiam

  • A hybrid multi-objective evolutionary algorithm for solving truck and trailer vehicle routing problems

    Kay Chen Tan;Yoong Han Chew;Loo Hay Lee

  • Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming

    Su Nguyen;Mengjie Zhang;Mark Johnston;Kay Chen Tan

  • Solving multiobjective vehicle routing problem with stochastic demand via evolutionary computation

    Kay Chen Tan;Chun Yew Cheong;Chi Keong Goh

  • Enhancing the firm's performance through quality and supply base management: An empirical study

    Keah-Choon Tan;Robert B. Handfield;D. R. Krause

  • A multiobjective evolutionary algorithm for solving vehicle routing problem with time windows

    K.C. Tan;T.H. Lee;Y.H. Chew;L.H. Lee

Frequent Co-Authors

Haizhou Li
Haizhou Li Chinese University of Hong Kong, Shenzhen
Mengjie Zhang
Mengjie Zhang Victoria University of Wellington
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Tong Heng Lee
Tong Heng Lee National University of Singapore
Su Nguyen
Su Nguyen RMIT University
Zhang Yi
Zhang Yi Sichuan University
Yun Li
Yun Li University of Electronic Science and Technology of China
Yew-Soon Ong
Yew-Soon Ong Nanyang Technological University
Loo Hay Lee
Loo Hay Lee National University of Singapore
Jian-Xin Xu
Jian-Xin Xu National University of Singapore

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