World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
37366
World Ranking
5994
National Ranking
794

Bo Chen 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 Bo Chen 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: 292 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.

Bo Chen 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 Bo Chen 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Bo Chen is affiliated with Xidian University in China and has contributed extensively to the fields of computer science and engineering. Their research outputs span multiple subfields including artificial intelligence, computer vision and pattern recognition, aerospace engineering, media technology, and biomedical engineering.

The main topics Bo Chen has explored include:

  • Multimodal Machine Learning Applications
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Advanced SAR Imaging Techniques
  • Natural Language Processing Techniques
  • Advanced Image and Video Retrieval Techniques
  • Underwater Acoustics Research

Bo Chen's publication record features several recent papers in notable venues, including:

  • FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion (2020), IEEE Transactions on Image Processing
  • Tensor RNN With Bayesian Nonparametric Mixture for Radar HRRP Modeling and Target Recognition (2021), IEEE Transactions on Signal Processing
  • Context-Specific Heterogeneous Graph Convolutional Network for Implicit Sentiment Analysis (2020), IEEE Access
  • Variational Temporal Deep Generative Model for Radar HRRP Target Recognition (2020), IEEE Transactions on Signal Processing
  • Multi scale investigation on the failure mechanism of adhesion between asphalt and aggregate caused by aging (2020), Construction and Building Materials

Frequent co-authors collaborating with Bo Chen include Hongwei Liu, Mingyuan Zhou, Hao Zhang, Ruiying Lu, and Zhengjue Wang.

Bo Chen frequently publishes in venues such as arXiv (Cornell University), Signal Processing, IEEE Transactions on Neural Networks and Learning Systems, SSRN Electronic Journal, and IEEE Transactions on Signal Processing.

Their primary fields of study are computer science, comprising 230 publications, and engineering, with 100 publications.

Best Publications

  • MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

    Andrew G. Howard;Menglong Zhu;Bo Chen;Dmitry Kalenichenko

  • Searching for MobileNetV3

    Andrew Howard;Ruoming Pang;Hartwig Adam;Quoc Le

  • MnasNet: Platform-Aware Neural Architecture Search for Mobile

    Mingxing Tan;Bo Chen;Ruoming Pang;Vijay Vasudevan

  • Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

    Benoit Jacob;Skirmantas Kligys;Bo Chen;Menglong Zhu

  • Learning Fine-Grained Image Similarity with Deep Ranking

    Jiang Wang;Yang Song;Thomas Leung;Chuck Rosenberg

  • Convolutional Neural Network With Data Augmentation for SAR Target Recognition

    Jun Ding;Bo Chen;Hongwei Liu;Mengyuan Huang

  • Searching for MobileNetV3.

    Andrew Howard;Mark Sandler;Grace Chu;Liang-Chieh Chen

  • NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications

    Tien-Ju Yang;Andrew G. Howard;Bo Chen;Xiao Zhang

  • An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis

    Raymond J. Langley;Raymond J. Langley;Ephraim L. Tsalik;Ephraim L. Tsalik;Jennifer C. Van Velkinburgh;Seth W. Glickman;Seth W. Glickman

  • MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks

    Ariel Gordon;Elad Eban;Ofir Nachum;Bo Chen

  • Radar HRRP target recognition with deep networks

    Bo Feng;Bo Chen;Hongwei Liu

  • Inductive Principles for Restricted Boltzmann Machine Learning

    Benjamin M. Marlin;Kevin Swersky;Bo Chen;Nando de Freitas

  • Simultaneous Multibeam Resource Allocation Scheme for Multiple Target Tracking

    Junkun Yan;Hongwei Liu;Bo Jiu;Bo Chen

  • Long short-term memory RNN for biomedical named entity recognition

    Chen Lyu;Bo Chen;Yafeng Ren;Donghong Ji

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

  • Deep Learning with Hierarchical Convolutional Factor Analysis

    Bo Chen;G. Polatkan;G. Sapiro;D. Blei

  • Prior Knowledge-Based Simultaneous Multibeam Power Allocation Algorithm for Cognitive Multiple Targets Tracking in Clutter

    Junkun Yan;Bo Jiu;Hongwei Liu;Bo Chen

  • Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS

    Gabriel Bender;Hanxiao Liu;Bo Chen;Grace Chu

  • FusionNet: An Unsupervised Convolutional Variational Network for Hyperspectral and Multispectral Image Fusion

    Zhengjue Wang;Bo Chen;Ruiying Lu;Hao Zhang

  • End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization

    Bo Chen;Alvaro Parra;Jiewei Cao;Nan Li

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

  • Deep Learning with

    Bo Chen;Guillermo Sapiro;David Blei;D avid Dunson

Frequent Co-Authors

Mingyuan Zhou
Mingyuan Zhou The University of Texas at Austin
Hongwei Liu
Hongwei Liu Xidian University
Zheng Bao
Zheng Bao Xidian University
Pietro Perona
Pietro Perona California Institute of Technology
Lawrence Carin
Lawrence Carin Duke University
Hartwig Adam
Hartwig Adam Google (United States)
Xin Yuan
Xin Yuan Nanyang Technological University
Mark Sandler
Mark Sandler Google (United States)
Yong-Chang Jiao
Yong-Chang Jiao Xidian University
Vijay K. Vasudevan
Vijay K. Vasudevan Google (United States)

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