World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
6547
World Ranking
8474
National Ranking
1106

Yong Qin publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Yong Qin sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 391 publications — 86th percentile

86% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Yong Qin D-index placement in Computer Science in 2026

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

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Yong Qin is affiliated with Lanzhou University in China and specializes in research primarily focused on engineering and materials science. Their scholarly contributions encompass a range of studies that intersect advanced sensing technologies, energy harvesting materials, and polymer science.

The main fields of study for Yong Qin include:

  • Engineering
  • Materials Science

Within these broader fields, Yong Qin has contributed significantly to the following subfields:

  • Biomedical Engineering
  • Polymers and Plastics
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Electronic, Optical and Magnetic Materials

The scientist's research focuses on several key topics, including:

  • Advanced Sensor and Energy Harvesting Materials
  • Conducting polymers and applications
  • Supercapacitor Materials and Fabrication
  • Innovative Energy Harvesting Technologies
  • Gas Sensing Nanomaterials and Sensors
  • Tactile and Sensory Interactions
  • Dielectric materials and actuators

Yong Qin has coauthored numerous papers with frequent collaborators such as Shuhai Liu, Qi Xu, Xiuhan Li, Suo Bai, and Juan Wen.

The scientist has published extensively in several venues. The most frequent publication outlets include:

  • Nano Energy
  • ACS Applied Materials & Interfaces
  • Nature Communications
  • SSRN Electronic Journal
  • Advanced Materials

Significant recent publications by Yong Qin include:

  • Flexoelectronics of centrosymmetric semiconductors, 2020, Nature Nanotechnology
  • Enhancing the current density of a piezoelectric nanogenerator using a three-dimensional intercalation electrode, 2020, Nature Communications
  • High performance temperature difference triboelectric nanogenerator, 2021, Nature Communications
  • Development and outlook of high output piezoelectric nanogenerators, 2021, Nano Energy
  • Highly sensitive strain sensors based on piezotronic tunneling junction, 2022, Nature Communications

Best Publications

  • Understanding and Learning Discriminant Features based on Multiattention 1DCNN for Wheelset Bearing Fault Diagnosis

    Huan Wang;Zhiliang Liu;Dandan Peng;Yong Qin

  • A Novel Deeper One-Dimensional CNN With Residual Learning for Fault Diagnosis of Wheelset Bearings in High-Speed Trains

    Dandan Peng;Zhiliang Liu;Huan Wang;Yong Qin

  • Multi-attribute group decision making models under interval type-2 fuzzy environment

    Unknown

  • A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral

    Weizhong Wang;Xinwang Liu;Yong Qin;Yong Fu

  • A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis

    Dong Wang;Dong Wang;Xuejun Zhao;Lin-Lin Kou;Yong Qin

  • Traffic zone division based on big data from mobile phone base stations

    Honghui Dong;Mingchao Wu;Xiaoqing Ding;Lianyu Chu

  • Real-time road traffic state prediction based on ARIMA and Kalman filter

    Dong-wei Xu;Yong-dong Wang;Li-min Jia;Yong Qin

  • Hybrid deep learning architecture for rail surface segmentation and surface defect detection

    Yunpeng Wu;Yunpeng Wu;Yong Qin;Yu Qian;Feng Guo

  • Feature-Level Attention-Guided Multitask CNN for Fault Diagnosis and Working Conditions Identification of Rolling Bearing.

    Huan Wang;Zhiliang Liu;Dandan Peng;Mei Yang

  • Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings

    Zhiliang Liu;Huan Wang;Junjie Liu;Yong Qin

  • Short-Term Abnormal Passenger Flow Prediction Based on the Fusion of SVR and LSTM

    Jianyuan Guo;Zhen Xie;Yong Qin;Limin Jia

  • A UAV-Based Visual Inspection Method for Rail Surface Defects

    Yunpeng Wu;Yong Qin;Zhipeng Wang;Limin Jia

  • Improved Hilbert-Huang transform with soft sifting stopping criterion and its application to fault diagnosis of wheelset bearings.

    Zhiliang Liu;Dandan Peng;Ming J. Zuo;Ming J. Zuo;Jianshuo Xia

  • Self-powered triboelectric nano vibration accelerometer based wireless sensor system for railway state health monitoring

    Xuejun Zhao;Guowu Wei;Xiuhan Li;Yong Qin

  • Optimal Number and Location Planning of Evacuation Signage in Public Space

    Zhe Zhang;Limin Jia;Yong Qin

  • A fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral

    Weizhong Wang;Xinwang Liu;Yong Qin

  • Remaining useful life prediction of rolling element bearings based on health state assessment

    Zhiliang Liu;Zhiliang Liu;Ming J Zuo;Ming J Zuo;Yong Qin

  • Automatic bearing fault diagnosis using particle swarm clustering and Hidden Markov Model

    Mitchell Yuwono;Yong Qin;Jing Zhou;Ying Guo

  • Interval-valued intuitionistic fuzzy aggregation operators

    Unknown

  • UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation

    Unknown

  • Roller bearing safety region estimation and state identification based on LMD–PCA–LSSVM

    Yuan Zhang;Yong Qin;Zong-yi Xing;Li-min Jia

  • Optimization of segmentation fragments in empirical wavelet transform and its applications to extracting industrial bearing fault features

    Dong Wang;Dong Wang;Kwok-Leung Tsui;Yong Qin

  • Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character

    Weizhong Wang;Xinwang Liu;Xiaoqing Chen;Yong Qin

Frequent Co-Authors

Limin Jia
Limin Jia Beijing Jiaotong University
Ming J. Zuo
Ming J. Zuo University of Alberta
Dong Wang
Dong Wang Shanghai Jiao Tong University
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Xuesong Zhou
Xuesong Zhou Arizona State University
Yang Zhao
Yang Zhao Beijing Institute of Technology
Ruisi He
Ruisi He Beijing Jiaotong University
Klaus Bengler
Klaus Bengler Technical University of Munich

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