World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
9238
World Ranking
6822
National Ranking
57

Yi-Hsuan Yang 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 Yi-Hsuan Yang 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: 231 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Yi-Hsuan Yang 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 Yi-Hsuan Yang 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Yi-Hsuan Yang is affiliated with National Taiwan University in Taiwan. Their research focuses primarily on computer science, with a significant number of publications in signal processing, computer vision and pattern recognition, cognitive neuroscience, artificial intelligence, and music.

Their main fields of study include:

  • Computer Science

The key subfields where Yi-Hsuan Yang has contributed are:

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Cognitive Neuroscience
  • Artificial Intelligence
  • Music

Major topics covered in their work include:

  • Music and Audio Processing
  • Music Technology and Sound Studies
  • Speech and Audio Processing
  • Neuroscience and Music Perception
  • Diverse Musicological Studies
  • Speech Recognition and Synthesis
  • Generative Adversarial Networks and Image Synthesis

Yi-Hsuan Yang has published extensively in various venues. The most frequent publication outlets are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Signal Processing Magazine
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Their recent research papers include:

  • "Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs", 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications", 2021, IEEE Signal Processing Magazine
  • "Theme Transformer: Symbolic Music Generation With Theme-Conditioned Transformer", 2022, IEEE Transactions on Multimedia
  • "Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions", 2020, arXiv (Cornell University)
  • "Benzimidazole Based Hole-Transporting Materials for High-performance Inverted Perovskite Solar Cells", 2022, Advanced Functional Materials

Frequent collaborators in Yi-Hsuan Yang's research include:

  • Wen-Yi Hsiao
  • Joann Ching
  • Boyu Chen
  • Shih-Lun Wu
  • Ching-Yu Chiu

Best Publications

  • A Regression Approach to Music Emotion Recognition

    Yi-Hsuan Yang;Yu-Ching Lin;Ya-Fan Su;H.H. Chen

  • MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and Accompaniment

    Hao-Wen Dong;Wen-Yi Hsiao;Li-Chia Yang;Yi-Hsuan Yang

  • Machine Recognition of Music Emotion: A Review

    Yi-Hsuan Yang;Homer H. Chen

  • MidiNet: A Convolutional Generative Adversarial Network for Symbolic-Domain Music Generation.

    Li-Chia Yang;Szu-Yu Chou;Yi-Hsuan Yang

  • Music emotion classification: a fuzzy approach

    Yi-Hsuan Yang;Chia-Chu Liu;Homer H. Chen

  • Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions

    Yu-Siang Huang;Yi-Hsuan Yang

  • Developing a benchmark for emotional analysis of music

    Anna Aljanaki;Yi Hsuan Yang;Mohammad Soleymani

  • 1000 songs for emotional analysis of music

    Mohammad Soleymani;Micheal N. Caro;Erik M. Schmidt;Cheng-Ya Sha

  • Music Emotion Recognition

    Yi-Hsuan Yang;Homer H. Chen

  • Ranking-Based Emotion Recognition for Music Organization and Retrieval

    Yi-Hsuan Yang;Homer H Chen

  • Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

    Wen-Yi Hsiao;Jen-Yu Liu;Yin-Cheng Yeh;Yi-Hsuan Yang

  • Vocal activity informed singing voice separation with the iKala dataset

    Tak-Shing Chan;Tzu-Chun Yeh;Zhe-Cheng Fan;Hung-Wei Chen

  • Music Emotion Recognition: Toward new, robust standards in personalized and context-sensitive applications

    Juan Sebastia Gomez-Canon;Estefania Cano;Tuomas Eerola;Perfecto Herrera

  • Fusion of electroencephalographic dynamics and musical contents for estimating emotional responses in music listening.

    Yuan-Pin Lin;Yi-Hsuan Yang;Tzyy-Ping Jung

  • Toward Multi-modal Music Emotion Classification

    Yi-Hsuan Yang;Yu-Ching Lin;Heng-Tze Cheng;I-Bin Liao

  • Automatic chord recognition for music classification and retrieval

    Heng-Tze Cheng;Yi-Hsuan Yang;Yu-Ching Lin;I-Bin Liao

  • Music emotion recognition: the role of individuality

    Yi-Hsuan Yang;Ya-Fan Su;Yu-Ching Lin;Homer H. Chen

  • Deep Learning for Audio-Based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach

    Juhan Nam;Keunwoo Choi;Jongpil Lee;Szu-Yu Chou

  • Collaborative Similarity Embedding for Recommender Systems

    Chih-Ming Chen;Chuan-Ju Wang;Ming-Feng Tsai;Yi-Hsuan Yang

  • Music Emotion Classification: A Regression Approach

    Yi-Hsuan Yang;Yu-Ching Lin;Ya-Fan Su;H.H. Chen

Frequent Co-Authors

Homer H. Chen
Homer H. Chen National Taiwan University
Hsin-Min Wang
Hsin-Min Wang Academia Sinica
Jyh-Shing Roger Jang
Jyh-Shing Roger Jang National Taiwan University
Mohammad Soleymani
Mohammad Soleymani University of Southern California
Chih-Ming Chen
Chih-Ming Chen National Chengchi University
Winston H. Hsu
Winston H. Hsu National Taiwan University
Xiao Hu
Xiao Hu University of Hong Kong
Hong-Yuan Mark Liao
Hong-Yuan Mark Liao Academia Sinica
Xavier Serra
Xavier Serra Pompeu Fabra University
Emilia Gómez
Emilia Gómez Pompeu Fabra University

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