World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
54
Citations
9198
World Ranking
3260
National Ranking
671

Yingfeng Zhang 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 Yingfeng Zhang 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: 201 publications — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Yingfeng Zhang 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 Yingfeng Zhang 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: 54 D-Index — 68th percentile

68% of scientists in this discipline score the same or lower.

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

Overview

Yingfeng Zhang is affiliated with Northwestern Polytechnical University in China and has a research focus primarily in engineering, with notable work in medicine as well. Their research spans multiple subfields, including industrial and manufacturing engineering, molecular biology, materials chemistry, mechanical engineering, and management of technology and innovation.

Their scholarly output is distributed among several key topics, reflecting an emphasis on both technological and scientific aspects of manufacturing and material sciences. Main topics include:

  • Digital Transformation in Industry
  • Manufacturing Process and Optimization
  • X-ray Diffraction in Crystallography
  • Crystallization and Solubility Studies
  • Flexible and Reconfigurable Manufacturing Systems
  • Sustainable Supply Chain Management
  • Product Development and Customization

Zhang's recent publications indicate active engagement with sustainable and smart manufacturing technologies. Selected papers include:

  • "A big data-driven framework for sustainable and smart additive manufacturing," 2020, Robotics and Computer-Integrated Manufacturing
  • "Data-driven sustainable intelligent manufacturing based on demand response for energy-intensive industries," 2020, Journal of Cleaner Production
  • "Digital twin-driven service model and optimal allocation of manufacturing resources in shared manufacturing," 2021, Journal of Manufacturing Systems
  • "CPS-Based Self-Adaptive Collaborative Control for Smart Production-Logistics Systems," 2020, IEEE Transactions on Cybernetics
  • "Big data driven predictive production planning for energy-intensive manufacturing industries," 2020, Energy

Their frequent coauthors reflect a consistent collaborative network. Regular collaborators include Amy V. Hall, Dmitry S. Yufit, Osama M. Musa, Jonathan W. Steed, and Geng Zhang.

In terms of publication venues, Zhang has contributed extensively to:

  • The Cambridge Structural Database
  • Advanced Engineering Informatics
  • Research Square (Research Square)
  • Robotics and Computer-Integrated Manufacturing
  • International Journal of Computer Integrated Manufacturing

The research contributions span quantitative and computational methods applied to industrial and manufacturing contexts, with intersections in molecular and materials chemistry. The work combines data-driven approaches and digital technologies to address manufacturing processes, optimization, and sustainable practices.

Best Publications

  • A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products

    Yingfeng Zhang;Shan Ren;Yang Liu;Yang Liu;Shubin Si

  • A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions

    Shan Ren;Yingfeng Zhang;Yang Liu;Yang Liu;Tomohiko Sakao

  • RFID-based wireless manufacturing for real-time management of job shop WIP inventories.

    George Q. Huang;YF Zhang;PY Jiang

  • Real-time information capturing and integration framework of the internet of manufacturing things

    Yingfeng Zhang;Geng Zhang;Junqiang Wang;Shudong Sun

  • A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT

    Yingfeng Zhang;Zhengang Guo;Jingxiang Lv;Ying Liu

  • Agent and Cyber-Physical System Based Self-Organizing and Self-Adaptive Intelligent Shopfloor

    Unknown

  • A big data-driven framework for sustainable and smart additive manufacturing

    Arfan Majeed;Yingfeng Zhang;Yingfeng Zhang;Shan Ren;Jingxiang Lv

  • RFID-based wireless manufacturing for walking-worker assembly islands with fixed-position layouts

    George Q. Huang;Y. F. Zhang;P. Y. Jiang

  • A framework for Big Data driven product lifecycle management

    Yingfeng Zhang;Shan Ren;Yang Liu;Yang Liu;Tomohiko Sakao

  • A big data driven analytical framework for energy-intensive manufacturing industries

    Yingfeng Zhang;Shuaiyin Ma;Haidong Yang;Jingxiang Lv

  • RFID-enabled real-time wireless manufacturing for adaptive assembly planning and control

    George Q. Huang;Yingfeng Zhang;X. Chen;Stephen T. Newman

  • Data-driven sustainable intelligent manufacturing based on demand response for energy-intensive industries

    Shuaiyin Ma;Yingfeng Zhang;Yang Liu;Yang Liu;Haidong Yang

  • An ‘Internet of Things’ enabled dynamic optimization method for smart vehicles and logistics tasks

    Sichao Liu;Yingfeng Zhang;Yingfeng Zhang;Yang Liu;Yang Liu;Lihui Wang

  • Research on services encapsulation and virtualization access model of machine for cloud manufacturing

    Yingfeng Zhang;Geng Zhang;Yang Liu;Di Hu

  • How can smart technologies contribute to sustainable product lifecycle management

    Yang Liu;Yingfeng Zhang;Shan Ren;Miying Yang

  • Game theory based real-time multi-objective flexible job shop scheduling considering environmental impact

    Yingfeng Zhang;Jin Wang;Yang Liu;Yang Liu

  • Digital twin-driven service model and optimal allocation of manufacturing resources in shared manufacturing

    Gang Wang;Geng Zhang;Xin Guo;Yingfeng Zhang

  • IoT-Enabled Real-Time Production Performance Analysis and Exception Diagnosis Model

    Yingfeng Zhang;Wenbo Wang;Naiqi Wu;Cheng Qian

  • CPS-Based Self-Adaptive Collaborative Control for Smart Production-Logistics Systems

    Zhengang Guo;Yingfeng Zhang;Xibin Zhao;Xiaoyu Song

  • Agent-based workflow management for RFID-enabled real-time reconfigurable manufacturing

    YingFeng Zhang;George Q. Huang;Ting Qu;Oscar Ho

  • Agent-based Smart Gateway for RFID-enabled real-time wireless manufacturing

    Yingfeng Zhang;T. Qu;Oscar K. Ho;George Q. Huang

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

    Bufan Liu;Yingfeng Zhang;Geng Zhang;Pai Zheng

  • Energy-cyber-physical system enabled management for energy-intensive manufacturing industries

    Shuaiyin Ma;Yingfeng Zhang;Jingxiang Lv;Haidong Yang

  • A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers

    T. Qu;H. D. Yang;George Q. Huang;Y. F. Zhang

  • The ‘Internet of Things’ enabled real-time scheduling for remanufacturing of automobile engines

    Yingfeng Zhang;Sichao Liu;Sichao Liu;Yang Liu;Yang Liu;Haidong Yang

Frequent Co-Authors

Yang Liu
Yang Liu Linköping University
George Q. Huang
George Q. Huang Hong Kong Polytechnic University
Fei Tao
Fei Tao Beihang University
Ray Y. Zhong
Ray Y. Zhong University of Hong Kong
Donald Huisingh
Donald Huisingh University of Tennessee at Knoxville
Xiongbiao Chen
Xiongbiao Chen University of Saskatchewan
Tomohiko Sakao
Tomohiko Sakao Linköping University
Lihui Wang
Lihui Wang Royal Institute of Technology
Yiming Rong
Yiming Rong Southern University of Science and Technology
Pai Zheng
Pai Zheng Hong Kong Polytechnic University

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