World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4974
World Ranking
12177
National Ranking
1503

Feng Jiang 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 Feng Jiang 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: 150 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Feng Jiang 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 Feng Jiang 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Feng Jiang is affiliated with the Harbin Institute of Technology in China and has contributed extensively to the fields of computer science and engineering. Their research primarily spans computer vision and pattern recognition, biomedical engineering, artificial intelligence, radiology, nuclear medicine and imaging, as well as cognitive neuroscience.

Their work involves several specific topics, including muscle activation and electromyography studies, prosthetics and rehabilitation robotics, image and signal denoising methods, anomaly detection techniques and applications, sparse and compressive sensing techniques, topic modeling, and stroke rehabilitation and recovery.

Feng Jiang has published numerous research papers in various respected venues. Some of the recent publications include:

  • "Skin lesion segmentation via generative adversarial networks with dual discriminators," 2020, Medical Image Analysis
  • "DFD-Net: lung cancer detection from denoised CT scan image using deep learning," 2020, Frontiers of Computer Science
  • "Image Compressed Sensing Using Non-Local Neural Network," 2021, IEEE Transactions on Multimedia
  • "Improving Entity Linking by Modeling Latent Entity Type Information," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Video Compressed Sensing Using a Convolutional Neural Network," 2020, IEEE Transactions on Circuits and Systems for Video Technology

Feng Jiang frequently publishes in venues such as arXiv (Cornell University), Sensors, SSRN Electronic Journal, IEEE Transactions on Multimedia, and IEEE Transactions on Circuits and Systems for Video Technology.

The scientist regularly collaborates with several co-authors, including Chunzhi Yi, Shaohui Liu, Chifu Yang, Zhen Ding, and Baichun Wei.

Best Publications

  • Image Compressed Sensing Using Convolutional Neural Network

    Wuzhen Shi;Feng Jiang;Shaohui Liu;Debin Zhao

  • Deep Learning Based Multi-Channel Intelligent Attack Detection for Data Security

    Feng Jiang;Yunsheng Fu;B. B. Gupta;Yongsheng Liang

  • An End-to-End Compression Framework Based on Convolutional Neural Networks

    Feng Jiang;Wen Tao;Shaohui Liu;Jie Ren

  • Medical image denoising using convolutional neural network: a residual learning approach

    Worku Jifara;Feng Jiang;Seungmin Rho;Maowei Cheng

  • Detection of abnormal heart conditions based on characteristics of ECG signals

    Mohamed Hammad;Mohamed Hammad;Asmaa Maher;Kuanquan Wang;Feng Jiang

  • Scalable Convolutional Neural Network for Image Compressed Sensing

    Wuzhen Shi;Feng Jiang;Shaohui Liu;Debin Zhao

  • Deep networks for compressed image sensing

    Wuzhen Shi;Feng Jiang;Shengping Zhang;Debin Zhao

  • Medical image semantic segmentation based on deep learning

    Feng Jiang;Aleksei Grigorev;Seungmin Rho;Zhihong Tian;Zhihong Tian

  • Robust Visual Tracking Using Structurally Random Projection and Weighted Least Squares

    Shengping Zhang;Huiyu Zhou;Feng Jiang;Xuelong Li

  • Brain Image Segmentation Based on FCM Clustering Algorithm and Rough Set

    Hong Huang;Fanzhi Meng;Shaohua Zhou;Feng Jiang

  • sEMG-Based Gesture Recognition with Convolution Neural Networks

    Zhen Ding;Chifu Yang;Zhihong Tian;Chunzhi Yi

  • Multi-layered gesture recognition with Kinect

    Feng Jiang;Shengping Zhang;Shen Wu;Yang Gao

  • Image Compressed Sensing Using Non-Local Neural Network

    Unknown

  • Single image super-resolution with dilated convolution based multi-scale information learning inception module

    Wuzhen Shi;Feng Jiang;Debin Zhao

  • Recurrent Neural Network Based Classification of ECG Signal Features for Obstruction of Sleep Apnea Detection

    Maowei Cheng;Worku J. Sori;Feng Jiang;Adil Khan

  • Convolutional Neural Networks Based Intra Prediction for HEVC

    Wenxue Cui;Tao Zhang;Shengping Zhang;Feng Jiang

  • Structural Group Sparse Representation for Image Compressive Sensing Recovery

    Jian Zhang;Debin Zhao;Feng Jiang;Wen Gao

  • Deep feature extraction and combination for synthetic aperture radar target classification

    Moussa Amrani;Feng Jiang

  • Improving Entity Linking by Modeling Latent Entity Type Information.

    Shuang Chen;Jinpeng Wang;Feng Jiang;Chin-Yew Lin

  • Very deep feature extraction and fusion for arrhythmias detection

    Moussa Amrani;Mohamed Hammad;Mohamed Hammad;Feng Jiang;Kuanquan Wang

  • ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question Answering

    Shuang Chen;Qian Liu;Zhiwei Yu;Chin-Yew Lin

  • Convolutional Neural Networks based Intra Prediction for HEVC

    Wenxue Cui;Tao Zhang;Shengping Zhang;Feng Jiang

Frequent Co-Authors

Debin Zhao
Debin Zhao Harbin Institute of Technology
Seungmin Rho
Seungmin Rho Chung-Ang University
Shengping Zhang
Shengping Zhang Harbin Institute of Technology
Zhihong Tian
Zhihong Tian Guangzhou University
Huiyu Zhou
Huiyu Zhou University of Leicester
Wen Gao
Wen Gao Peking University
Kuanquan Wang
Kuanquan Wang Harbin Institute of Technology
Hongxun Yao
Hongxun Yao Harbin Institute of Technology
Brij B. Gupta
Brij B. Gupta Asia University Taiwan
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology

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