World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6744
World Ranking
8880
National Ranking
1146

Xiao Hu 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 Xiao Hu 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: 293 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Xiao Hu 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 Xiao Hu 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Xiao Hu is affiliated with the University of Hong Kong in China. Their research spans interdisciplinary domains with a focus on medicine, engineering, and neuroscience. They have contributed extensively to several subfields, notably biomedical engineering, cognitive neuroscience, rehabilitation, computer vision and pattern recognition, and neurology.

The core research topics addressed by Xiao Hu include stroke rehabilitation and recovery, muscle activation and electromyography studies, EEG and brain-computer interfaces, transcranial magnetic stimulation studies, neuroscience and neural engineering, advanced wireless communication technologies, and indoor and outdoor localization technologies.

Recent publications by Xiao Hu illustrate a focus on upper limb rehabilitation and neuromuscular control after stroke. Selected papers include:

  • An Exoneuromusculoskeleton for Self-Help Upper Limb Rehabilitation After Stroke (2020, Soft Robotics)
  • Altered Corticomuscular Coherence (CMCoh) Pattern in the Upper Limb During Finger Movements After Stroke (2020, Frontiers in Neurology)
  • Home-based self-help telerehabilitation of the upper limb assisted by an electromyography-driven wrist/hand exoneuromusculoskeleton after stroke (2021, Journal of NeuroEngineering and Rehabilitation)
  • Pathway-specific cortico-muscular coherence in proximal-to-distal compensation during fine motor control of finger extension after stroke (2021, Journal of Neural Engineering)
  • A Data-Driven Investigation on Surface Electromyography Based Clinical Assessment in Chronic Stroke (2021, Frontiers in Neurorobotics)

Xiao Hu frequently publishes in venues such as arXiv (Cornell University), Frontiers in Aging Neuroscience, Journal of Neural Engineering, Frontiers in Bioengineering and Biotechnology, and Lecture Notes in Computer Science.

Collaborative work is marked by repeated coauthorship with researchers including Yanhuan Huang, Fuqiang Ye, Bibo Yang, Zengyong Li, and Shaomin Zhang. These collaborations have supported contributions across multiple studies and publications.

Best Publications

  • Mining correlated bursty topic patterns from coordinated text streams

    Xuanhui Wang;ChengXiang Zhai;Xiao Hu;Richard Sproat

  • Photoplethysmography based atrial fibrillation detection: a review.

    Tania Pereira;Nate Tran;Kais Gadhoumi;Michele M. Pelter

  • The 2007 MIREX Audio Mood Classification Task: Lessons Learned

    Xiao Hu;J. Stephen Downie;Cyril Laurier;Mert Bay

  • Improving mood classification in music digital libraries by combining lyrics and audio

    Xiao Hu;J. Stephen Downie

  • Exploring Mood Metadata: Relationships with Genre, Artist and Usage Metadata.

    Xiao Hu;J. Stephen Downie

  • Understanding the nature of learners’ out-of-class language learning experience with technology

    Chun Lai;Xiao Hu;Boning Lyu

  • Morphological Clustering and Analysis of Continuous Intracranial Pressure

    Xiao Hu;Peng Xu;F. Scalzo;P. Vespa

  • LYRIC TEXT MINING IN MUSIC MOOD CLASSIFICATION

    Xiao Hu;J. Stephen Downie;Andreas F. Ehmann

  • When Lyrics Outperform Audio for Music Mood Classification: A Feature Analysis.

    Xiao Hu;J. Stephen Downie

  • Technologic Distractions (Part 1): Summary of Approaches to Manage Alert Quantity With Intent to Reduce Alert Fatigue and Suggestions for Alert Fatigue Metrics.

    Sandra L. Kane-Gill;Michael F. O’Connor;Jeffrey M. Rothschild;Nicholas M. Selby

  • Exploring the relationship between social presence and learners’ prestige in MOOC discussion forums using automated content analysis and social network analysis

    Wenting Zou;Xiao Hu;Zilong Pan;Chenglu Li

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

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

  • Forecasting ICP Elevation Based on Prescient Changes of Intracranial Pressure Waveform Morphology

    Xiao Hu;Peng Xu;Shadnaz Asgari;Paul Vespa

  • Clinical information system

    Valeriy Nenov;Xiao Hu;Cho-Nan Tsai

  • The influence of individual espoused cultural values on self-directed use of technology for language learning beyond the classroom

    Chun Lai;Qiu Wang;Xiaoshi Li;Xiao Hu

  • The effects of stimulus timing features on P300 speller performance

    Jessica Lu;William Speier;Xiao Hu;Nader Pouratian

  • Multivariate AR modeling of electromyography for the classification of upper arm movements.

    Xiao Hu;Valeriy Nenov

  • Cross-Dataset and Cross-Cultural Music Mood Prediction: A Case on Western and Chinese Pop Songs

    Xiao Hu;Yi-Hsuan Yang

  • Intracranial Pressure Pulse Morphological Features Improved Detection of Decreased Cerebral Blood Flow

    Xiao Hu;Thomas Glenn;Fabien Scalzo;Marvin Bergsneider

  • Voice-Controlled Clinical Information Dashboard

    Valeriy I. Nenov;Neil A. Martin;Xiao Hu;Farzad D. Buxey

  • University students’ use of music for learning and well-being: A qualitative study and design implications

    Xiao Hu;Jing Chen;Yuhao Wang

Frequent Co-Authors

Paul M. Vespa
Paul M. Vespa University of California, Los Angeles
Peng Xu
Peng Xu Chinese Academy of Sciences
Neil A. Martin
Neil A. Martin University of California, Los Angeles
Marek Czosnyka
Marek Czosnyka University of Cambridge
David S. Liebeskind
David S. Liebeskind University of California, Los Angeles
Shawn C. Shadden
Shawn C. Shadden University of California, Berkeley
Yi-Hsuan Yang
Yi-Hsuan Yang National Taiwan University
Nader Pouratian
Nader Pouratian University of California, Los Angeles
Peter Smielewski
Peter Smielewski University of Cambridge
Christine Miaskowski
Christine Miaskowski University of California, San Francisco

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