World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
34
Citations
4338
World Ranking
2880
National Ranking
357

Kun-Peng Zhu publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Kun-Peng Zhu sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 106 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Kun-Peng Zhu D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Kun-Peng Zhu sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 34 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Best Publications

  • Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results

    Kunpeng Zhu;Yoke San Wong;Geok Soon Hong

  • Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring

    Yingjie Zhang;Geok Soon Hong;Dongsen Ye;Kunpeng Zhu

  • Defect detection in selective laser melting technology by acoustic signals with deep belief networks

    Dongsen Ye;Geok Soon Hong;Yingjie Zhang;Kunpeng Zhu

  • Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

    Kunpeng Zhu;Yoke San Wong;Geok Soon Hong

  • A generic tool wear model and its application to force modeling and wear monitoring in high speed milling

    Unknown

  • Online Tool Wear Monitoring Via Hidden Semi-Markov Model With Dependent Durations

    Unknown

  • A Review of Spatter in Laser Powder Bed Fusion Additive Manufacturing: In Situ Detection, Generation, Effects, and Countermeasures

    Unknown

  • The monitoring of micro milling tool wear conditions by wear area estimation

    Unknown

  • In situ monitoring of selective laser melting using plume and spatter signatures by deep belief networks.

    Dongsen Ye;Jerry Ying Hsi Fuh;Yingjie Zhang;Geok Soon Hong

  • A machine vision system for micro-milling tool condition monitoring

    Unknown

  • Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks

    Yingjie Zhang;Hong Geok Soon;Dongsen Ye;Jerry Ying Hsi Fuh

  • Sensor fusion for online tool condition monitoring in milling

    W. H. Wang;G. S. Hong;Y. S. Wong;K. P. Zhu

  • A generic instantaneous undeformed chip thickness model for the cutting force modeling in micromilling

    Unknown

  • Tool wear estimation and life prognostics in milling: Model extension and generalization

    Unknown

  • Big Data Oriented Smart Tool Condition Monitoring System

    Unknown

  • Online condition monitoring in micro-milling: A force waveform shape analysis approach

    Unknown

  • The investigation of plume and spatter signatures on melted states in selective laser melting

    Dongsen Ye;Dongsen Ye;Dongsen Ye;Kunpeng Zhu;Jerry Ying Hsi Fuh;Yingjie Zhang

  • Interpretable deep learning approach for tool wear monitoring in high-speed milling

    Unknown

  • Diagnosis and Prognosis of Degradation Process via Hidden Semi-Markov Model

    Unknown

  • An Adaptive Activation Transfer Learning Approach for Fault Diagnosis

    Unknown

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Related Online Degrees & Career Pathways

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Considering these correlated degrees can enrich your engineering career, offering skills that bridge technical and human-centered approaches in the evolving aerospace and mechanical industries.

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