World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
6830
World Ranking
7289
National Ranking
93

Geok Soon Hong 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 Geok Soon Hong 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: 152 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Geok Soon Hong 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 Geok Soon Hong 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: 40 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Geok Soon Hong is affiliated with the National University of Singapore in Singapore. Their research spans the field of engineering, with a focus on mechanical engineering, biomedical engineering, control and systems engineering, automotive engineering, and industrial and manufacturing engineering.

Their main research topics include:

  • Advanced machining processes and optimization
  • Advanced surface polishing techniques
  • Photoacoustic and ultrasonic imaging
  • Nanoplatforms for cancer theranostics
  • Photodynamic therapy research studies
  • Mineral processing and grinding
  • Fault detection and control systems

Geok Soon Hong has published in a variety of venues with differing focuses, reflecting the interdisciplinary nature of their work. These venues include:

  • Angewandte Chemie International Edition
  • Rapid Prototyping Journal
  • Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
  • Manufacturing Letters
  • International Journal of Machine Learning and Computing

Recent papers authored or co-authored by Geok Soon Hong highlight applications and advancements across engineering and biomedical fields. Select publications include:

  • "Boosting Photoacoustic Effect via Intramolecular Motions Amplifying Thermal-to-Acoustic Conversion Efficiency for Adaptive Image-Guided Cancer Surgery," 2021, published in Angewandte Chemie International Edition

Geok Soon Hong has collaborated frequently with other researchers, including:

  • Heting Hong
  • Chengwen Luo
  • Xingchen Duan
  • Yi Zeng
  • Xiaoyan Zheng

The range of their published research exhibits work related to improving manufacturing processes, monitoring systems, and biomedical imaging techniques. Example publications in related topics include studies on data fusion analysis for additive manufacturing process monitoring and energy storage system management strategies for electric vehicles.

Best Publications

  • An Overview of 3D Printing Technologies for Food Fabrication

    Jie Sun;Weibiao Zhou;Dejian Huang;Jerry Y. H. Fuh

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

    Kunpeng Zhu;Yoke San Wong;Geok Soon Hong

  • A Review on 3D Printing for Customized Food Fabrication

    Jie Sun;Zhuo Peng;Weibiao Zhou;Jerry Y.H. Fuh

  • 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

  • A Cost-Sensitive Deep Belief Network for Imbalanced Classification

    Chong Zhang;Kay Chen Tan;Haizhou Li;Geok Soon Hong

  • 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

  • 3D food printing an innovative way of mass customization in food fabrication

    Jie Sun;Zhuo Peng;Liangkun Yan;Jerry Ying Hsi Fuh

  • Nozzle condition monitoring in 3D printing

    Yedige Tlegenov;Geok Soon Hong;Wen Feng Lu

  • Multiclassification of tool wear with support vector machine by manufacturing loss consideration

    J Sun;M Rahman;Y.S Wong;G.S Hong

  • 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

  • Profile error compensation in fast tool servo diamond turning of micro-structured surfaces

    De Ping Yu;Geok Soon Hong;Yoke San Wong

  • Machine Selection Rules in a Dynamic Job Shop

    V. Subramaniam;G. K. Lee;T. Ramesh;G. S. Hong

  • Flank wear measurement by a threshold independent method with sub-pixel accuracy

    W.H. Wang;G.S. Hong;Y.S. Wong

  • Flank wear measurement by successive image analysis

    W. Wang;Y. S. Wong;G. S. Hong

  • Series damper actuator: a novel force/torque control actuator

    Chee-Meng Chew;Geok-Soon Hong;Wei Zhou

  • Bayesian-inference-based neural networks for tool wear estimation

    Jianfei Dong;K. V. R. Subrahmanyam;Yoke San Wong;Geok Soon Hong

  • Sensor fusion for online tool condition monitoring in milling

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

  • Optimized tool path generation for fast tool servo diamond turning of micro-structured surfaces

    De Ping Yu;De Ping Yu;Sze Wei Gan;Yoke San Wong;Geok Soon Hong

  • In-situ monitoring of laser-based PBF via off-axis vision and image processing approaches

    Yingjie Zhang;Jerry Y.H. Fuh;Dongsen Ye;Geok Soon Hong

  • Using neural network for tool condition monitoring based on wavelet decomposition

    G.S. Hong;M. Rahman;Q. Zhou

Frequent Co-Authors

Yoke San Wong
Yoke San Wong National University of Singapore
Jerry Y. H. Fuh
Jerry Y. H. Fuh National University of Singapore
Marcelo H. Ang
Marcelo H. Ang National University of Singapore
Wen Feng Lu
Wen Feng Lu National University of Singapore
Haizhou Li
Haizhou Li Chinese University of Hong Kong, Shenzhen
Chee-Kong Chui
Chee-Kong Chui National University of Singapore
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
M. Rahman
M. Rahman National University of Singapore
Weibiao Zhou
Weibiao Zhou National University of Singapore
Sunan Huang
Sunan Huang National University of Singapore

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