World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
13558
World Ranking
4050
National Ranking
1929

Feng Zhou 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 Zhou 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.

Feng Zhou 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 Zhou 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: 56 D-Index — 72nd percentile

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

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

Overview

Feng Zhou is affiliated with the University of Michigan-Ann Arbor in the United States. Their research activities primarily focus on the field of Engineering, contributing extensively to multiple subfields including Social Psychology, Artificial Intelligence, Materials Chemistry, Safety, Risk, Reliability and Quality, and Automotive Engineering.

The scientist's work spans several core topics such as Human-Automation Interaction and Safety, Traffic and Road Safety, Sleep and Work-Related Fatigue, Autonomous Vehicle Technology and Safety, Crystallization and Solubility Studies, X-ray Diffraction in Crystallography, and Safety Warnings and Signage.

Feng Zhou has published numerous papers in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • The Cambridge Structural Database
  • SSRN Electronic Journal
  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting
  • IEEE Transactions on Intelligent Transportation Systems

Some of the recent papers authored or co-authored by Feng Zhou are:

  • Using Eye-Tracking Data to Predict Situation Awareness in Real Time During Takeover Transitions in Conditionally Automated Driving, 2021, IEEE Transactions on Intelligent Transportation Systems
  • Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving, 2020, Transportation Research Part C Emerging Technologies
  • Predicting driver takeover performance in conditionally automated driving, 2020, Accident Analysis & Prevention

The scientist has collaborated frequently with several co-authors, including:

  • X. Jessie Yang
  • Baiying Lei
  • Lilit Avetisyan
  • Jackie Ayoub
  • Na Du

Best Publications

  • Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR

    Feng Zhou;Henry Been-Lirn Duh;Mark Billinghurst

  • Detecting depression from facial actions and vocal prosody

    Jeffrey F. Cohn;Tomas Simon Kruez;Iain Matthews;Ying Yang

  • Searching Central Difference Convolutional Networks for Face Anti-Spoofing

    Zitong Yu;Chenxu Zhao;Zezheng Wang;Yunxiao Qin

  • MagFace: A Universal Representation for Face Recognition and Quality Assessment

    Qiang Meng;Shichao Zhao;Zhida Huang;Feng Zhou

  • Deep Metric Learning with Angular Loss

    Jian Wang;Feng Zhou;Shilei Wen;Xiao Liu

  • Factorized Graph Matching

    Feng Zhou;Fernando De la Torre

  • Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion

    Feng Zhou;F. De la Torre;J. K. Hodgins

  • Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

    Ming Sun;Yuchen Yuan;Feng Zhou;Errui Ding

  • Kernel Pooling for Convolutional Neural Networks

    Yin Cui;Feng Zhou;Jiang Wang;Xiao Liu

  • Canonical Time Warping for Alignment of Human Behavior

    Feng Zhou;Fernando Torre

  • Deep Learning Framework for Alzheimer’s Disease Diagnosis via 3D-CNN and FSBi-LSTM

    Chiyu Feng;Ahmed Elazab;Peng Yang;Tianfu Wang

  • Fine-Grained Categorization and Dataset Bootstrapping Using Deep Metric Learning with Humans in the Loop

    Yin Cui;Feng Zhou;Yuanqing Lin;Serge Belongie

  • Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features

    Zhen Yu;Xudong Jiang;Feng Zhou;Jing Qin

  • Aligned Cluster Analysis for temporal segmentation of human motion

    Feng Zhou;F. Torre;J.K. Hodgins

  • Embedding Label Structures for Fine-Grained Feature Representation

    Xiaofan Zhang;Feng Zhou;Yuanqing Lin;Shaoting Zhang

  • Deep Spatial Gradient and Temporal Depth Learning for Face Anti-Spoofing

    Zezheng Wang;Zitong Yu;Chenxu Zhao;Xiangyu Zhu

  • Generalized time warping for multi-modal alignment of human motion

    Feng Zhou;Fernando De la Torre

  • Fine-Grained Image Classification by Exploring Bipartite-Graph Labels

    Feng Zhou;Yuanqing Lin

  • Deformable Graph Matching

    Feng Zhou;Fernando De la Torre

  • Learning meta model for zero- and few-shot face anti-spoofing

    Yunxiao Qin;Chenxu Zhao;Xiangyu Zhu;Zezheng Wang

  • Affective and cognitive design for mass personalization: status and prospect

    Feng Zhou;Yangjian Ji;Roger Jianxin Jiao

Frequent Co-Authors

Baiying Lei
Baiying Lei Shenzhen University
Tianfu Wang
Tianfu Wang Shenzhen University
Fernando De la Torre
Fernando De la Torre Carnegie Mellon University
Xiao Liu
Xiao Liu Baidu (China)
Dawn M. Tilbury
Dawn M. Tilbury University of Michigan–Ann Arbor
Errui Ding
Errui Ding Baidu (China)
Yuanqing Lin
Yuanqing Lin Aibee Inc.
Dong Ni
Dong Ni Shenzhen University
Zhen Lei
Zhen Lei Chinese Academy of Sciences
Jing Qin
Jing Qin Hong Kong Polytechnic University

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