World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4455
World Ranking
12242
National Ranking
1507

Xintao 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 Xintao 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: 157 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Xintao 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 Xintao 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: 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

Xintao Hu is affiliated with Northwestern Polytechnical University in China and has contributed extensively to the fields of neuroscience and artificial intelligence. Their research spans multiple subfields including cognitive neuroscience, computer vision, radiology, nuclear medicine, imaging, and electrical and electronic engineering.

The main areas of study focus on functional brain connectivity, neural dynamics and brain function, EEG and brain-computer interfaces, topic modeling, advanced neuroimaging techniques, visual attention and saliency detection, and advanced memory and neural computing.

Xintao Hu has published frequently in several venues, with the highest number of publications appearing in arXiv (Cornell University), followed by Frontiers in Neuroscience, bioRxiv (Cold Spring Harbor Laboratory), UNC Libraries, and IEEE Transactions on Cognitive and Developmental Systems.

Their recent notable papers include:

  • When brain-inspired AI meets AGI (2023), Meta-Radiology
  • Hyperspectral anomaly detection using ensemble and robust collaborative representation (2023), Information Sciences
  • Test-retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging (2021), Human Brain Mapping
  • Understanding LLMs: A comprehensive overview from training to inference (2024), Neurocomputing
  • Understanding Llms: A Comprehensive Overview from Training to Inference (2024), SSRN Electronic Journal

The scientist has collaborated frequently with several researchers, including Tianming Liu, Dajiang Zhu, Tuo Zhang, Xi Jiang, and Lin Zhao.

Best Publications

  • Background Prior-Based Salient Object Detection via Deep Reconstruction Residual

    Junwei Han;Dingwen Zhang;Xintao Hu;Lei Guo

  • Sparse representation of whole-brain fMRI signals for identification of functional networks.

    Jinglei Lv;Xi Jiang;Xiang Li;Dajiang Zhu

  • Representing and Retrieving Video Shots in Human-Centric Brain Imaging Space

    Junwei Han;Xiang Ji;Xintao Hu;Dajiang Zhu

  • Object detection in remote sensing imagery using a discriminatively trained mixture model

    Gong Cheng;Junwei Han;Lei Guo;Xiaoliang Qian

  • Modeling Task fMRI Data Via Deep Convolutional Autoencoder

    Heng Huang;Xintao Hu;Yu Zhao;Milad Makkie

  • DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

    Dajiang Zhu;Kaiming Li;Kaiming Li;Lei Guo;Xi Jiang

  • Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

    Jiahui Wang;Yudan Ren;Xintao Hu;Vinh Thai Nguyen

  • Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function

    Jinglei Lv;Xi Jiang;Xiang Li;Dajiang Zhu

  • Fusing DTI and fMRI data: A survey of methods and applications

    Dajiang Zhu;Tuo Zhang;Xi Jiang;Xintao Hu

  • Support vector machine multiparametric MRI identification of pseudoprogression from tumor recurrence in patients with resected glioblastoma.

    Xintao Hu;Kelvin K. Wong;Geoffrey S. Young;Lei Guo

  • Axonal Fiber Terminations Concentrate on Gyri

    Jingxin Nie;Lei Guo;Kaiming Li;Kaiming Li;Yonghua Wang

  • The integration of the internal and external milieu in the insula during dynamic emotional experiences.

    Vinh Thai Nguyen;Michael Breakspear;Xintao Hu;Christine Cong Guo

  • Weakly supervised target detection in remote sensing images based on transferred deep features and negative bootstrapping

    Peicheng Zhou;Gong Cheng;Zhenbao Liu;Shuhui Bu

  • Automatic Recognition of fMRI-Derived Functional Networks Using 3-D Convolutional Neural Networks

    Yu Zhao;Qinglin Dong;Shu Zhang;Wei Zhang

  • Coevolution of Gyral Folding and Structural Connection Patterns in Primate Brains

    Hanbo Chen;Tuo Zhang;Tuo Zhang;Lei Guo;Kaiming Li;Kaiming Li

  • Supervised Dictionary Learning for Inferring Concurrent Brain Networks

    Shijie Zhao;Junwei Han;Jinglei Lv;Xi Jiang

  • Learning Computational Models of Video Memorability from fMRI Brain Imaging

    Junwei Han;Changyuan Chen;Ling Shao;Xintao Hu

  • Latent source mining in FMRI via restricted Boltzmann machine

    Xintao Hu;Heng Huang;Bo Peng;Junwei Han

  • Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

    Kaiming Li;Lei Guo;Carlos Faraco;Dajiang Zhu

  • Task fMRI data analysis based on supervised stochastic coordinate coding

    Jinglei Lv;Binbin Lin;Qingyang Li;Wei Zhang

  • Self-organized interdependence among populations promotes cooperation by means of coevolution.

    Chen Chu;Xintao Hu;Chen Shen;Tong Li

Frequent Co-Authors

Tianming Liu
Tianming Liu University of Georgia
Lei Guo
Lei Guo Beijing University of Posts and Telecommunications
Junwei Han
Junwei Han Northwestern Polytechnical University
Kaiming Li
Kaiming Li Sichuan University
Dajiang Zhu
Dajiang Zhu The University of Texas at Arlington
Stephen T. C. Wong
Stephen T. C. Wong Houston Methodist
Xiaoping Hu
Xiaoping Hu University of California, Riverside
Vincent Mok
Vincent Mok Chinese University of Hong Kong
Adrian Wong
Adrian Wong Chinese University of Hong Kong
Lingjiang Li
Lingjiang Li Central South University

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