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2025

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Rising Stars

D-Index
39
Citations
5591
World Ranking
695
National Ranking
241

Computer Science

D-Index
43
Citations
6933
World Ranking
8044
National Ranking
1056

Pai Zheng 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 Pai Zheng 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: 102 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Pai Zheng 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 Pai Zheng 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Pai Zheng is affiliated with the Hong Kong Polytechnic University in China. Their research primarily spans the field of Engineering, with a focus on Industrial and Manufacturing Engineering, Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, and Marketing.

The scientist's work covers several main topics, including:

  • Digital Transformation in Industry
  • Manufacturing Process and Optimization
  • Robot Manipulation and Learning
  • Industrial Vision Systems and Defect Detection
  • Service and Product Innovation
  • Flexible and Reconfigurable Manufacturing Systems
  • Additive Manufacturing and 3D Printing Technologies

Pai Zheng has contributed to numerous frequent publication venues, such as:

  • Journal of Manufacturing Systems
  • Robotics and Computer-Integrated Manufacturing
  • Advanced Engineering Informatics
  • Journal of Cleaner Production
  • Journal of Intelligent Manufacturing

Recent papers highlight various aspects of manufacturing and Industry 5.0, including:

  • Industry 5.0: Prospect and retrospect, 2022, Journal of Manufacturing Systems
  • Industry 5.0 and Society 5.0-Comparison, complementation and co-evolution, 2022, Journal of Manufacturing Systems
  • Human Digital Twin in the context of Industry 5.0, 2023, Robotics and Computer-Integrated Manufacturing
  • Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective, 2022, Journal of Manufacturing Systems
  • Deep reinforcement learning in smart manufacturing: A review and prospects, 2022, CIRP journal of manufacturing science and technology

In their collaborations, Pai Zheng has frequently co-authored with the following researchers:

  • Lihui Wang
  • Chun-Hsien Chen
  • Shufei Li
  • Junming Fan
  • Liqiao Xia

Best Publications

  • Smart manufacturing systems for Industry 4.0: Conceptual framework, scenarios, and future perspectives

    Pai Zheng;Honghui wang;Zhiqian Sang;Runyang Zhong

  • A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives

    Kendrik Yan Hong Lim;Pai Zheng;Pai Zheng;Chun Hsien Chen

  • A systematic design approach for service innovation of smart product-service systems

    Pai Zheng;Pai Zheng;Tzu Jui Lin;Chun Hsien Chen;Xun Xu

  • A survey of smart product-service systems: Key aspects, challenges and future perspectives

    Pai Zheng;Zuoxu Wang;Chun Hsien Chen;Li Pheng Khoo

  • Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach

    Pai Zheng;Liqiao Xia;Chengxi Li;Xinyu Li;Xinyu Li

  • Towards proactive human–robot collaboration: A foreseeable cognitive manufacturing paradigm

    Shufei Li;Ruobing Wang;Pai Zheng;Lihui Wang

  • A digital twin-enhanced system for engineering product family design and optimization

    Kendrik Yan Hong Lim;Pai Zheng;Chun Hsien Chen;Lihui Huang

  • A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment

    Pai Zheng;Pai Zheng;Xun Xu;Chun-Hsien Chen

  • A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

    Zuoxu Wang;Chun Hsien Chen;Pai Zheng;Xinyu Li

  • A Knowledge Graph-Aided Concept–Knowledge Approach for Evolutionary Smart Product–Service System Development

    Xinyu Li;Xinyu Li;Chun Hsien Chen;Pai Zheng;Zuoxu Wang

  • A generic tri-model-based approach for product-level digital twin development in a smart manufacturing environment

    Pai Zheng;Abinav Shankar Sivabalan

  • Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network

    Jingchao Jiang;Guobiao Hu;Xiao Li;Xun Xu

  • Smart, connected open architecture product : an IT-driven co-creation paradigm with lifecycle personalization concerns

    Pai Zheng;Pai Zheng;Yuan Lin;Chun Hsien Chen;Xun Xu

  • A smart surface inspection system using faster R-CNN in cloud-edge computing environment

    Yuanbin Wang;Minggao Liu;Pai Zheng;Huayong Yang

  • Edge-cloud orchestration driven industrial smart product-service systems solution design based on CPS and IIoT

    Bufan Liu;Yingfeng Zhang;Geng Zhang;Pai Zheng

  • Exploiting knowledge graphs in industrial products and services: A survey of key aspects, challenges, and future perspectives

    Xinyu Li;Mengtao Lyu;Zuoxu Wang;Chun Hsien Chen

  • Towards Proactive Human Robot Collaborative Assembly: A Multimodal Transfer Learning-Enabled Action Prediction Approach

    Shufei Li;Pai Zheng;Junming Fan;Lihui Wang

  • A data-driven reversible framework for achieving Sustainable Smart product-service systems

    Xinyu Li;Zuoxu Wang;Chun Hsien Chen;Pai Zheng

  • Towards an automatic engineering change management in smart product-service systems – A DSM-based learning approach

    Pai Zheng;Chun-Hsien Chen;Suiyue Shang

  • A graph-based context-aware requirement elicitation approach in smart product-service systems

    Zuoxu Wang;Chun-Hsien Chen;Pai Zheng;Pai Zheng;Xinyu Li

  • Personalized product configuration framework in an adaptable open architecture product platform

    Pai Zheng;Xun Xu;Shiqiang Yu;Chao Liu

Frequent Co-Authors

Chun-Hsien Chen
Chun-Hsien Chen Nanyang Technological University
Xun Xu
Xun Xu University of Auckland
Li Pheng Khoo
Li Pheng Khoo Nanyang Technological University
Ray Y. Zhong
Ray Y. Zhong University of Hong Kong
Lihui Wang
Lihui Wang Royal Institute of Technology
Soo Jay Phee
Soo Jay Phee Nanyang Technological University
Yingfeng Zhang
Yingfeng Zhang Northwestern Polytechnical University
Etienne Burdet
Etienne Burdet Imperial College London
Lin Zhang
Lin Zhang Beihang University
Sheng Quan Xie
Sheng Quan Xie University of Leeds

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