World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
32
Citations
4067
World Ranking
6342
National Ranking
905

Qiuqiang Kong publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Qiuqiang Kong sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 446 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 139 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Qiuqiang Kong D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Qiuqiang Kong sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 263 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Best Publications

  • PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition

    Qiuqiang Kong;Yin Cao;Turab Iqbal;Yuxuan Wang

  • Large-Scale Weakly Supervised Audio Classification Using Gated Convolutional Neural Network

    Yong Xu;Qiuqiang Kong;Wenwu Wang;Mark D. Plumbley

  • Sound Event Detection of Weakly Labelled Data With CNN-Transformer and Automatic Threshold Optimization

    Qiuqiang Kong;Yong Xu;Wenwu Wang;Mark D. Plumbley

  • Audio Set Classification with Attention Model: A Probabilistic Perspective

    Qiuqiang Kong;Yong Xu;Wenwu Wang;Mark D. Plumbley

  • AudioLDM 2: Learning Holistic Audio Generation With Self-Supervised Pretraining

    Unknown

  • Convolutional gated recurrent neural network incorporating spatial features for audio tagging

    Yong Xu;Qiuqiang Kong;Qiang Huang;Wenwu Wang

  • Deep Neural Network Baseline for DCASE Challenge 2016

    Qiuqiang Kong;Iwona Sobieraj;Wenwu Wang;Mark Plumbley

  • Multi-level attention model for weakly supervised audio classification

    Changsong Yu;Karim Said Barsim;Qiuqiang Kong;Bin Yang

  • An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection

    Yin Cao;Turab Iqbal;Qiuqiang Kong;Fengyan An

  • PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition

    Qiuqiang Kong;Yin Cao;Turab Iqbal;Yuxuan Wang

  • Polyphonic Sound Event Detection and Localization using a Two-Stage Strategy.

    Yin Cao;Qiuqiang Kong;Turab Iqbal;Fengyan An

  • High-resolution Piano Transcription with Pedals by Regressing Onsets and Offsets Times

    Qiuqiang Kong;Bochen Li;Xuchen Song;Yuan Wan

  • Attention and Localization based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging

    Yong Xu;Qiuqiang Kong;Qiang Huang;Wenwu Wang

  • VoiceFixer: A Unified Framework for High-Fidelity Speech Restoration

    Unknown

  • Audio for Audio is Better? An Investigation on Transfer Learning Models for Heart Sound Classification

    Tomoya Koike;Kun Qian;Qiuqiang Kong;Mark D. Plumbley

  • Separate What You Describe: Language-Queried Audio Source Separation

    Unknown

  • A joint detection-classification model for audio tagging of weakly labelled data

    Qiuqiang Kong;Yong Xu;Wenwu Wang;Mark D. Plumbley

  • Attention-based Atrous Convolutional Neural Networks: Visualisation and Understanding Perspectives of Acoustic Scenes

    Zhao Ren;Qiuqiang Kong;Jing Han;Mark D. Plumbley

  • Weakly Labelled AudioSet Tagging with Attention Neural Networks

    Qiuqiang Kong;Changsong Yu;Turab Iqbal;Yong Xu

  • Attention-based Convolutional Neural Networks for Acoustic Scene Classification

    Zhao Ren;Qiuqiang Kong;Kun Qian;Mark D Plumbley

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Related Online Degrees & Career Pathways

For those interested in expanding their expertise beyond traditional electronics and electrical engineering, exploring related online degrees can open new career opportunities. Programs like an instructional design degree online offer a pathway into educational technology and development, supporting engineering professionals who want to design training materials or corporate learning programs.

Many online education programs now utilize competency based programs, allowing learners to progress at their own pace by demonstrating their skills. This approach is especially beneficial for working engineers seeking flexible and efficient ways to earn advanced credentials.

Military families can also benefit from tailored opportunities. Resources like the military spouse online college guide highlight institutions that accommodate the unique lifestyle and mobility challenges faced by military spouses and dependents, helping them pursue degrees in engineering-related fields without interruption.

Lastly, enrolling in online universities with multiple start dates provides added flexibility for students balancing work, life, and study. These frequent start options ensure that prospective learners can begin their education when it suits them best, which is crucial for adult learners and professionals in the engineering sector.

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