World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
85
Citations
29563
World Ranking
802
National Ranking
436

Xiaoming Liu 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 Xiaoming Liu 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: 296 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Xiaoming Liu 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 Xiaoming Liu 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: 85 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Overview

Xiaoming Liu is affiliated with Michigan State University in the United States. Their research spans multiple disciplines within the broad areas of Agricultural and Biological Sciences and Biochemistry, Genetics and Molecular Biology.

The scientist's publication record includes work primarily focused on food science and related biological fields. Key subfields of study include Food Science, Molecular Biology, Nutrition and Dietetics, Genetics, and Infectious Diseases.

Their research topics are centered on several domains:

  • Probiotics and Fermented Foods
  • Gut microbiota and health
  • Protein Hydrolysis and Bioactive Peptides
  • Proteins in Food Systems
  • Infant Nutrition and Health
  • Digestive system and related health
  • Composting and Vermicomposting Techniques

Frequent co-authors collaborating with Liu include:

  • Peng Zhou
  • Jianxin Zhao
  • Bo Yang
  • Wei Chen
  • Dasong Liu

Liu has contributed papers to several notable publication venues. Among the most frequent are:

  • Food Bioscience
  • International Dairy Journal
  • Foods
  • Food Hydrocolloids
  • Food Science and Human Wellness

Representative recent papers authored or co-authored by Liu include:

  • "Effects of nitrogen fertilizer and chemical regulation on spring maize lodging characteristics, grain filling and yield formation under high planting density in Heilongjiang Province, China" (2021), published in Journal of Integrative Agriculture
  • "Alkali lignin and sodium lignosulfonate additives promote the formation of humic substances during paper mill sludge composting" (2020), published in Bioresource Technology

Other notable publications connected to Liu's research network focus on gastrointestinal effects, electron transfer capacity in organic matter during composting, and the influence of capsaicin on gut microbiota, reflecting a diverse interest in both agricultural techniques and food-related health science.

Best Publications

  • Image Super-Resolution via Deep Recursive Residual Network

    Ying Tai;Jian Yang;Xiaoming Liu

  • MemNet: A Persistent Memory Network for Image Restoration

    Ying Tai;Jian Yang;Xiaoming Liu;Chunyan Xu

  • Face Alignment Across Large Poses: A 3D Solution

    Xiangyu Zhu;Zhen Lei;Xiaoming Liu;Hailin Shi

  • Disentangled Representation Learning GAN for Pose-Invariant Face Recognition

    Luan Tran;Xi Yin;Xiaoming Liu

  • Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision

    Yaojie Liu;Amin Jourabloo;Xiaoming Liu

  • On the Detection of Digital Face Manipulation

    Hao Dang;Feng Liu;Joel Stehouwer;Xiaoming Liu

  • Synthesis of the H-cluster framework of iron-only hydrogenase

    Cédric Tard;Xiaoming Liu;Saad K. Ibrahim;Maurizio Bruschi

  • FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

    Yu Chen;Ying Tai;Xiaoming Liu;Chunhua Shen

  • CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

    Yuge Huang;Yuhan Wang;Ying Tai;Xiaoming Liu

  • M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

    Garrick Brazil;Xiaoming Liu

  • Face anti-spoofing using patch and depth-based CNNs

    Yousef Atoum;Yaojie Liu;Amin Jourabloo;Xiaoming Liu

  • A 2D azine-linked covalent organic framework for gas storage applications

    Zhongping Li;Xiao Feng;Yongcun Zou;Yuwei Zhang

  • Face Alignment in Full Pose Range: A 3D Total Solution

    Xiangyu Zhu;Xiaoming Liu;Zhen Lei;Stan Z. Li

  • Video-based face recognition using adaptive hidden Markov models

    Xiaoming Liu;Tsuhan Cheng

  • Nonlinear 3D Face Morphable Model

    Luan Tran;Xiaoming Liu

  • Demographic Estimation from Face Images: Human vs. Machine Performance

    Hu Han;Charles Otto;Xiaoming Liu;Anil K. Jain

  • Towards Large-Pose Face Frontalization in the Wild

    Xi Yin;Xiang Yu;Kihyuk Sohn;Xiaoming Liu

  • Large-Pose Face Alignment via CNN-Based Dense 3D Model Fitting

    Amin Jourabloo;Xiaoming Liu

  • A robust and luminescent covalent organic framework as a highly sensitive and selective sensor for the detection of Cu(2+) ions.

    Zhongping Li;Yuwei Zhang;Hong Xia;Ying Mu

  • Feature Transfer Learning for Face Recognition With Under-Represented Data

    Xi Yin;Xiang Yu;Kihyuk Sohn;Xiaoming Liu

  • On Geometric Features for Skeleton-Based Action Recognition Using Multilayer LSTM Networks

    Songyang Zhang;Xiaoming Liu;Jun Xiao

Frequent Co-Authors

Peter Henry Tu
Peter Henry Tu General Electric (United States)
Joe M. Regenstein
Joe M. Regenstein Cornell University
Xiaoli Tan
Xiaoli Tan Iowa State University
Ying Tai
Ying Tai Nanjing University
Hao Zhang
Hao Zhang Jiangnan University
Tsuhan Chen
Tsuhan Chen Cornell University
Jianxin Zhao
Jianxin Zhao University of Queensland
Miaofang Chi
Miaofang Chi Oak Ridge National Laboratory
Yueting Zhuang
Yueting Zhuang Zhejiang University
Manmohan Chandraker
Manmohan Chandraker University of California, San Diego

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