World's Best Scientists 2026 revealed!

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 53 4911 4775 660 656 235 8921

Kaizhou Gao publications per year

The chart shows the history of publications by Kaizhou Gao between 2007 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Kaizhou Gao published across 19 years, from 2007 to 2025, averaging 15.6 papers a year. Output peaked at 54 publications in 2024. 101 of the 297 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 2007 to 2025. Vertical axis: number of publications, 0 to 54. Peak 54 publications in 2024. 2007: 7 publications 2008: 6 publications 2009: 3 publications 2010: 9 publications 2011: 10 publications 2012: 5 publications 2013: 10 publications 2014: 1 publication 2015: 6 publications 2016: 14 publications 2017: 15 publications 2018: 5 publications 2019: 15 publications 2020: 13 publications 2021: 19 publications 2022: 23 publications 2023: 35 publications 2024: 54 publications 2025: 47 publications
2007 2025

297 publications in total across all disciplines

View publications per year as a table
Kaizhou Gao: publications per year, 2007 to 2025
Year Publications
2007 7
2008 6
2009 3
2010 9
2011 10
2012 5
2013 10
2014 1
2015 6
2016 14
2017 15
2018 5
2019 15
2020 13
2021 19
2022 23
2023 35
2024 54
2025 47
Total 297
Download as CSV

Kaizhou Gao 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 Kaizhou Gao 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, 232–241 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: 235 publications — 58th percentile

58% 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
232–241 423 235
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
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
Download as CSV

Kaizhou Gao 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 Kaizhou Gao 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, 52–53 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: 53 D-Index — 67th percentile

67% 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 53
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
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
Download as CSV

Overview

Kaizhou Gao is affiliated with Macau University of Science and Technology in China. Their research work is primarily situated within the field of Engineering, with a strong emphasis on Industrial and Manufacturing Engineering as well as Control and Systems Engineering.

The scientist's contributions extend notably into the domain of Artificial Intelligence and Computer Networks and Communications, reflecting a multidisciplinary approach to complex engineering problems.

Kaizhou Gao's research topics cover a variety of subjects, including:

  • Scheduling and Optimization Algorithms
  • Advanced Manufacturing and Logistics Optimization
  • Assembly Line Balancing Optimization
  • Vehicle Routing Optimization Methods
  • Manufacturing Process and Optimization
  • Transportation Planning and Optimization
  • Optimization and Search Problems

Frequent collaborative partnerships have been established with researchers such as Yaping Fu, Yuyan Han, Junqing Li, Ponnuthurai Nagaratnam Suganthan, and Yuting Wang.

The scientist has published extensively in several scholarly venues, with a notable concentration of works appearing in:

  • Swarm and Evolutionary Computation
  • Expert Systems with Applications
  • Applied Soft Computing
  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE Transactions on Systems Man and Cybernetics Systems

Key recent papers authored or co-authored by Kaizhou Gao include:

  • "Distributed scheduling problems in intelligent manufacturing systems," 2021, Tsinghua Science & Technology
  • "A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem," 2020, IEEE Transactions on Intelligent Transportation Systems
  • "An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems," 2022, IEEE Transactions on Systems Man and Cybernetics Systems
  • "A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem," 2021, IEEE Transactions on Automation Science and Engineering
  • "A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances," 2022, IEEE Transactions on Intelligent Transportation Systems

Best Publications

  • A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems

    Kaizhou Gao;Zhiguang Cao;Le Zhang;Zhenghua Chen

  • Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems

    Jun-Qing Li;Quan-Ke Pan;Quan-Ke Pan;Kai-Zhou Gao

  • Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions

    Jun-qing Li;Jun-qing Li;Jun-qing Li;Hong-yan Sang;Yu-yan Han;Cun-gang Wang

  • Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm

    Kaizhou Gao;Fajun Yang;MengChu Zhou;Quanke Pan

  • A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Tay Jin Chua;Chin Soon Chong

  • A review of energy-efficient scheduling in intelligent production systems

    Kaizhou Gao;Kaizhou Gao;Yun Huang;Ali Sadollah;Ling Wang

  • Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling

    Kai-Zhou Gao;Kai-Zhou Gao;Ponnuthurai N. Suganthan;Quan-Ke Pan;Tay Jin Chua

  • Discrete harmony search algorithm for flexible job shop scheduling problem with multiple objectives

    K. Z. Gao;P. N. Suganthan;Q. K. Pan;T. J. Chua

  • Distributed Scheduling Problems in Intelligent Manufacturing Systems

    Yaping Fu;Yushuang Hou;Zifan Wang;Xinwei Wu

  • An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Tay Jin Chua

  • Novel MILP and CP models for distributed hybrid flowshop scheduling problem with sequence-dependent setup times

    Unknown

  • An Improved Artificial Bee Colony Algorithm With Q-Learning for Solving Permutation Flow-Shop Scheduling Problems

    Unknown

  • Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion

    Kai Zhou Gao;Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Mehmet Fatih Tasgetiren

  • A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem

    Palwasha W. Shaikh;Mohammed El-Abd;Mounib Khanafer;Kaizhou Gao

  • A Hybrid Iterated Greedy Algorithm for a Crane Transportation Flexible Job Shop Problem

    Jun-Qing Li;Yu Du;Kai-Zhou Gao;Pei-Yong Duan

  • Effective invasive weed optimization algorithms for distributed assembly permutation flowshop problem with total flowtime criterion

    Hong-Yan Sang;Quan-Ke Pan;Jun-Qing Li;Ping Wang

  • A genetic programming hyper-heuristic approach for the multi-skill resource constrained project scheduling problem

    Jian Lin;Lei Zhu;Kaizhou Gao;Kaizhou Gao

  • A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances

    Unknown

  • Effective metaheuristics for scheduling a hybrid flowshop with sequence-dependent setup times

    Quan-Ke Pan;Liang Gao;Xin-Yu Li;Kai-Zhou Gao

  • A survey on meta-heuristics for solving disassembly line balancing, planning and scheduling problems in remanufacturing

    Kai-Zhou Gao;Kai-Zhou Gao;Z. M. He;Y. Huang;Pei-Yong Duan

  • Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion

    Kai-zhou Gao;Quan-ke Pan;Jun-qing Li

  • Discrete evolutionary multi-objective optimization for energy-efficient blocking flow shop scheduling with setup time

    Yuyan Han;Junqing Li;Junqing Li;Hongyan Sang;Yiping Liu

  • An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time

    Kai Zhou Gao;Ponnuthurai Nagaratnam Suganthan;Quan Ke Pan;Mehmet Fatih Tasgetiren

Frequent Co-Authors

Junqing Li
Junqing Li Liaocheng University
Quan-Ke Pan
Quan-Ke Pan Shanghai University
Rong Su
Rong Su Nanyang Technological University
Yi Zhang
Yi Zhang Nanyang Technological University
NaiQi Wu
NaiQi Wu Macau University of Science and Technology
Jing Liang
Jing Liang Zhengzhou University
Ling Wang
Ling Wang Tsinghua University
Le Zhang
Le Zhang University of Electronic Science and Technology of China
MengChu Zhou
MengChu Zhou New Jersey Institute of Technology

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

Exploring Computer Science in the USA opens doors to a variety of related fields and interdisciplinary career paths. Many students consider pursuing online degrees in complementary subjects to enhance their skill set and improve career prospects.

For those interested in sustainable technology, environmental engineering degrees online offer coursework in cutting-edge topics like clean energy and green infrastructure. This specialization blends well with computer science skills in data analysis and automation.

Students often research the mechanical engineering cost of education to compare affordability and gain hands-on technical skills that are highly valued in robotics, manufacturing, and technology sectors.

Another popular option is earning online physics degrees, which provide a strong analytical foundation for careers in AI, software development, or research.

Finally, those focused on data careers can benefit from pursuing the cheapest data science masters in usa, gaining expertise in big data, machine learning, and analytics. This pathway is a natural extension for computer science graduates looking to specialize.

Best Scientists Citing Kaizhou Gao

Trending Scientists

Recently Published Articles