World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
37
Citations
5500
World Ranking
2515
National Ranking
128

Computer Science

D-Index
51
Citations
8880
World Ranking
5405
National Ranking
724

Ping Ji publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Ping Ji sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 141 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Ping Ji D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Ping Ji sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 37 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Ping Ji is affiliated with Hong Kong Polytechnic University in China and has contributed extensively to the field of Engineering, with a focus on several subfields including Industrial and Manufacturing Engineering, Biomedical Engineering, Electrical and Electronic Engineering, Civil and Structural Engineering, and Artificial Intelligence.

Their research spans a diverse range of topics including:

  • Nanoplatforms for cancer theranostics
  • Sustainable Supply Chain Management
  • Advanced Manufacturing and Logistics Optimization
  • Supply Chain and Inventory Management
  • Nanoparticle-Based Drug Delivery
  • Antibiotic Resistance in Bacteria
  • Cancer, Hypoxia, and Metabolism

Ping Ji has published papers in various scientific journals, with frequent publication venues including:

  • Remote Sensing
  • SSRN Electronic Journal
  • Nano Letters
  • One Health Advances
  • Advanced Engineering Informatics

Among recent publications authored or co-authored by Ping Ji are:

  • Digital twin modeling, 2022, Journal of Manufacturing Systems
  • Platform logistics or self-logistics? Restaurants' cooperation with online food-delivery platform considering profitability and sustainability, 2021, International Journal of Production Economics
  • Current status and trends of antimicrobial resistance among clinical isolates in China: a retrospective study of CHINET from 2018 to 2022, 2023, One Health Advances
  • Hydrogel systems for targeted cancer therapy, 2023, Frontiers in Bioengineering and Biotechnology
  • Self-Assembled Copper-Based Nanoparticles for Glutathione Activated and Enzymatic Cascade-Enhanced Ferroptosis and Immunotherapy in Cancer Treatment, 2023, Small

Frequent collaborators include Xian-Zheng Zhang, C.K.M. Lee, Fupin Hu, Yan Jin, and Jingzheng Ren, who have co-authored multiple works alongside Ping Ji.

Best Publications

  • The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis

    Kevin Cullinane;Teng-Fei Wang;Dong-Wook Song;Ping Ji

  • Activity recognition with smartphone sensors

    Xing Su;Hanghang Tong;Ping Ji

  • An Application of DEA Windows Analysis to Container Port Production Efficiency

    Kevin Cullinane;Dong-Wook Song;Ping Ji;Teng-Fei Wang

  • A hybrid genetic algorithm for the multi-depot vehicle routing problem

    William Ho;George T. S. Ho;Ping Ji;Henry C. W. Lau

  • The relationship between privatization and DEA estimates of efficiency in the container port industry

    Kevin Cullinane;Ping Ji;Teng-fei Wang

  • Understanding customer needs through quantitative analysis of Kano's model

    Ting Wang;Ping Ji

  • Identifying helpful online reviews: A product designer's perspective

    Ying Liu;Jian Jin;Ping Ji;Jenny A. Harding

  • Understanding big consumer opinion data for market-driven product design

    Jian Jin;Ying Liu;Ping Ji;Hongguang Liu

  • Identifying comparative customer requirements from product online reviews for competitor analysis

    Jian Jin;Ping Ji;Rui Gu

  • A comparison of hard-state and soft-state signaling protocols

    Ping Ji;Zihui Ge;Jim Kurose;Don Towsley

  • Cyber-physical integration for moving digital factories forward towards smart manufacturing: a survey

    Ying Cheng;Ying Cheng;Yongping Zhang;Ping Ji;Wenjun Xu

  • The evolutionary complexity of complex adaptive supply networks: A simulation and case study

    Gang Li;Hongjiao Yang;Linyan Sun;Ping Ji

  • Quantification and integration of Kano’s model into QFD for optimising product design

    Ping Ji;Jian Jin;Ting Wang;Yizeng Chen

  • A mixed integer programming model for advanced planning and scheduling (APS)

    Kejia Chen;Ping Ji

  • Scale transitivity in the AHP

    Ping Ji;R. Jiang

  • Aging property of unimodal failure rate models

    R. Jiang;Ping Ji;X. Xiao

  • Positioning multiple decoupling points in a supply network

    X.Y. Sun;P. Ji;L.Y. Sun;Y.L. Wang

  • Coordination of the closed-loop supply chain for product line design with consideration of remanufactured products

    R. Aydin;Chun Kit Kwong;Ping Ji

  • Models involving two inverse Weibull distributions

    Renyan Jiang;D. N. P. Murthy;Ping Ji

  • Component scheduling for chip shooter machines: a hybrid genetic algorithm approach

    William Ho;Ping Ji

  • An improved approach for failure mode and effect analysis involving large group of experts: An application to the healthcare field

    Hu Chen Liu;Xiao Yue You;Fugee Tsung;Ping Ji

Frequent Co-Authors

Ji-Bo Wang
Ji-Bo Wang Shenyang Aerospace University
William Ho
William Ho University of Melbourne
Wing Bun Lee
Wing Bun Lee Hong Kong Polytechnic University
Carman K. M. Lee
Carman K. M. Lee Hong Kong Polytechnic University
Fei Tao
Fei Tao Beihang University
Kevin Cullinane
Kevin Cullinane University of Gothenburg
Srinivas Talluri
Srinivas Talluri Michigan State University
D. N. P. Murthy
D. N. P. Murthy University of Queensland
Richard Y. K. Fung
Richard Y. K. Fung City University of Hong Kong
Baozhuang Niu
Baozhuang Niu South China University of Technology

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