World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
42
Citations
4973
World Ranking
6762
National Ranking
1266

Hong Peng 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 Hong Peng 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: 232 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Hong Peng 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 Hong Peng 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: 42 D-Index — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Overview

Hong Peng is a researcher affiliated with Xihua University in China. Their academic work spans multiple disciplines, primarily situated within Computer Science and Engineering, with significant contributions to Biochemistry, Genetics and Molecular Biology.

Themes central to their research include DNA and Biological Computing, Advanced Memory and Neural Computing, and Advanced Biosensing and Bioanalysis Techniques. They have also extensively explored Neural Networks and Reservoir Computing, Neural Networks and Applications, Modular Robots and Swarm Intelligence, as well as Cellular Automata and Applications.

Peng's frequent publishing outlets reflect their interdisciplinary approach, with numerous papers in the following venues:

  • International Journal of Neural Systems
  • Journal of Membrane Computing
  • Neural Networks
  • SSRN Electronic Journal
  • Knowledge-Based Systems

The researcher's recent prominent publications include:

  • "A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies," 2020, Engineering Applications of Artificial Intelligence
  • "Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain," 2020, International Journal of Neural Systems
  • "A novel fusion method based on dynamic threshold neural P systems and nonsubsampled contourlet transform for multi-modality medical images," 2020, Signal Processing
  • "LSTM-SNP: A long short-term memory model inspired from spiking neural P systems," 2021, Knowledge-Based Systems
  • "Multi-focus image fusion based on dynamic threshold neural P systems and surfacelet transform," 2020, Knowledge-Based Systems

Collaboration has been a consistent element in their career. Key frequent co-authors include:

  • Jun Wang
  • Zhicai Liu
  • Qian Yang
  • Xiaohui Luo
  • Mario J. Pérez-Jiménez

The scientist's research integrates computational models inspired by neural processes and biological systems, with a substantial focus on spiking neural P systems and neural network methodologies. Their work addresses applications in fault diagnosis, medical image fusion, and bioinformatics.

Best Publications

  • Formation of tough interlocking microstructures in silicon nitride ceramics by dynamic ripening

    Zhijian Shen;Zhe Zhao;Hong Peng;Mats Nygren

  • Ubiquitylation of Autophagy Receptor Optineurin by HACE1 Activates Selective Autophagy for Tumor Suppression

    Zhengzhao Liu;Peng Chen;Peng Chen;Hong Gao;Yu Gu

  • Fuzzy reasoning spiking neural P system for fault diagnosis

    Hong Peng;Jun Wang;Mario J. PéRez-JiméNez;Hao Wang

  • De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2

    Thomas W. Linsky;Renan Vergara;Nuria Codina;Jorgen W. Nelson

  • Weighted Fuzzy Spiking Neural P Systems

    Jun Wang;Peng Shi;Hong Peng;M. J. Perez-Jimenez

  • Ubiquitylation of p62/sequestosome1 activates its autophagy receptor function and controls selective autophagy upon ubiquitin stress

    Hong Peng;Jiao Yang;Jiao Yang;Guangyi Li;Guangyi Li;Qing You;Qing You

  • Fault Diagnosis of Power Systems Using Intuitionistic Fuzzy Spiking Neural P Systems

    Hong Peng;Jun Wang;Jun Ming;Peng Shi

  • Spiking neural P systems with multiple channels

    Hong Peng;Jinyu Yang;Jun Wang;Tao Wang

  • Dynamic threshold neural P systems

    Hong Peng;Jun Wang;Mario J. Pérez-Jiménez;Agustín Riscos-Núñez

  • Nonlinear Spiking Neural P Systems.

    Hong Peng;Zeqiong Lv;Bo Li;Xiaohui Luo

  • Coupled Neural P Systems

    Hong Peng;Jun Wang

  • Identification of recurrent USP48 and BRAF mutations in Cushing’s disease

    Jianhua Chen;Xuemin Jian;Siyu Deng;Zengyi Ma

  • Image watermarking method in multiwavelet domain based on support vector machines

    Hong Peng;Jun Wang;Weixing Wang

  • Membrane computing and image processing: a short survey

    Unknown

  • Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain.

    Bo Li;Hong Peng;Xiaohui Luo;Jun Wang

  • Nanobubbles do not sit alone at the solid-liquid interface.

    Hong Peng;Marc A. Hampton;Anh V. Nguyen

  • Spiking neural P systems with inhibitory rules

    Hong Peng;Bo Li;Jun Wang;Xiaoxiao Song

  • Formidable Increase in the Superplasticity of Ceramics in the Presence of an Electric Field

    Y. Zhijian Shen;Hong Peng;Mats Nygren

  • A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies

    Tao Wang;Xiaoguang Wei;Jun Wang;Tao Huang

  • A novel fusion method based on dynamic threshold neural P systems and nonsubsampled contourlet transform for multi-modality medical images

    Bo Li;Hong Peng;Jun Wang

  • An unsupervised learning algorithm for membrane computing

    Hong Peng;Jun Wang;Mario J. Pérez-Jiménez;Agustín Riscos-Núñez

  • Monolayer g-C3N4 Fluorescent Sensor for Sensitive and Selective Colorimetric Detection of Silver ion from Aqueous Samples

    Unknown

  • Conversion from nano- to micron-sized structures: experimental observations

    Zhijian Shen;Hong Peng;Jing Liu;Mats Nygren

  • LSTM-SNP: A long short-term memory model inspired from spiking neural P systems

    Qian Liu;Lifan Long;Qian Yang;Hong Peng

  • Adaptive fuzzy spiking neural P systems for fuzzy inference and learning

    Jun Wang;Hong Peng

  • Multiobjective fuzzy clustering approach based on tissue-like membrane systems

    Hong Peng;Peng Shi;Jun Wang;Agustn Riscos-Nez

  • Dendrite P systems.

    Hong Peng;Tingting Bao;Xiaohui Luo;Jun Wang

  • Multi-focus image fusion based on dynamic threshold neural P systems and surfacelet transform

    Bo Li;Hong Peng;Jun Wang;Xiangnian Huang

Frequent Co-Authors

Mario J. Pérez-Jiménez
Mario J. Pérez-Jiménez University of Seville
Mats Nygren
Mats Nygren Stockholm University
Peng Shi
Peng Shi University of Adelaide
Anh V. Nguyen
Anh V. Nguyen University of Queensland
Guanzhou Qiu
Guanzhou Qiu Central South University
Zhijian Shen
Zhijian Shen Stockholm University
Deyin Guo
Deyin Guo Sun Yat-sen University
Oksana Lockridge
Oksana Lockridge University of Nebraska Medical Center
Wenqing Qin
Wenqing Qin Central South University

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