World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
15863
World Ranking
3781
National Ranking
110

Lina Yao 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 Lina Yao 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.

Lina Yao 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 Lina Yao 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Lina Yao is a researcher affiliated with the Commonwealth Scientific and Industrial Research Organisation in Australia, focusing on the intersection of medicine and biochemistry, genetics, and molecular biology. Their research spans several subfields, including molecular biology, oncology, surgery, physiology, and pulmonary and respiratory medicine.

Their scientific output notably centers on topics such as drug transport and resistance mechanisms, adenosine and purinergic signaling, gut microbiota and health, pediatric hepatobiliary diseases and treatments, diet and metabolism studies, cancer mechanisms and therapy, and nuclear receptors and signaling.

Recent publications by Lina Yao include:

  • Human gut bacteria produce ΤΗ17-modulating bile acid metabolites, 2022, Nature
  • A bacterial bile acid metabolite modulates Treg activity through the nuclear hormone receptor NR4A1, 2021, Cell Host & Microbe
  • A microbial metabolite remodels the gut-liver axis following bariatric surgery, 2021, Cell Host & Microbe
  • Development of a covalent inhibitor of gut bacterial bile salt hydrolases, 2020, Nature Chemical Biology
  • A biosynthetic pathway for the selective sulfonation of steroidal metabolites by human gut bacteria, 2022, Nature Microbiology

Lina Yao frequently publishes in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature
  • Cell Host & Microbe
  • Developmental & Comparative Immunology
  • Nature Chemical Biology

Frequent collaborators include:

  • A. Sloan Devlin
  • Jun R. Huh
  • Donggi Paik
  • Yancong Zhang
  • Sena Bae

Best Publications

  • Deep Learning Based Recommender System: A Survey and New Perspectives

    Shuai Zhang;Lina Yao;Aixin Sun;Yi Tay

  • Adversarially regularized graph autoencoder for graph embedding

    Shirui Pan;Ruiqi Hu;Guodong Long;Jing Jiang

  • Deep Learning based Recommender System: A Survey and New Perspectives.

    Shuai Zhang;Lina Yao;Aixin Sun

  • Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges, and Opportunities

    Kaixuan Chen;Dalin Zhang;Lina Yao;Bin Guo

  • Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

    Lei Bai;Lina Yao;Can Li;Xianzhi Wang

  • Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition

    Dalin Zhang;Lina Yao;Kaixuan Chen;Sen Wang

  • A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition

    Kaixuan Chen;Lina Yao;Dalin Zhang;Xianzhi Wang

  • Quaternion Knowledge Graph Embeddings

    Shuai Zhang;Yi Tay;Lina Yao;Qi Liu

  • STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting

    Lei Bai;Lina Yao;Salil S. Kanhere;Xianzhi Wang

  • A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers.

    Xiang Zhang;Lina Yao;Xianzhi Wang;Jessica J M Monaghan

  • Unified Collaborative and Content-Based Web Service Recommendation

    Lina Yao;Quan Z. Sheng;Anne. H.H. Ngu;Jian Yu

  • CloudArmor: Supporting Reputation-Based Trust Management for Cloud Services

    Talal H. Noor;Quan Z. Sheng;Lina Yao;Schahram Dustdar

  • A Convolutional Recurrent Attention Model for Subject-Independent EEG Signal Analysis

    Dalin Zhang;Lina Yao;Kaixuan Chen;Jessica Monaghan

  • Momentum Contrastive Learning for Few-Shot COVID-19 Diagnosis from Chest CT Images

    Xiaocong Chen;Lina Yao;Tao Zhou;Jinming Dong

  • AutoSVD++: An Efficient Hybrid Collaborative Filtering Model via Contractive Auto-encoders

    Shuai Zhang;Lina Yao;Xiwei Xu

  • Motor Imagery Classification via Temporal Attention Cues of Graph Embedded EEG Signals

    Dalin Zhang;Kaixuan Chen;Debao Jian;Lina Yao

  • MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation

    Manqing Dong;Feng Yuan;Lina Yao;Xiwei Xu

  • Residual Attention U-Net for Automated Multi-Class Segmentation of COVID-19 Chest CT Images

    Xiaocong Chen;Lina Yao;Yu Zhang

  • DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns

    Feng Yuan;Lina Yao;Boualem Benatallah

  • A Survey on Deep Learning based Brain Computer Interface: Recent Advances and New Frontiers.

    Xiang Zhang;Lina Yao;Xianzhi Wang;Jessica Monaghan

  • Recommending Web Services via Combining Collaborative Filtering with Content-Based Features

    Lina Yao;Quan Z. Sheng;Aviv Segev;Jian Yu

  • Cascade and Parallel Convolutional Recurrent Neural Networks on EEG-based Intention Recognition for Brain Computer Interface.

    Dalin Zhang;Lina Yao;Xiang Zhang;Sen Wang

  • Cascade and Parallel Convolutional Recurrent Neural Networks on EEG-based Intention Recognition for Brain Computer Interface

    Dalin Zhang;Lina Yao;Xiang Zhang;Sen Wang

Frequent Co-Authors

Quan Z. Sheng
Quan Z. Sheng Macquarie University
Xiang Zhang
Xiang Zhang University of Hong Kong
Boualem Benatallah
Boualem Benatallah Dublin City University
Xue Li
Xue Li University of Queensland
Salil S. Kanhere
Salil S. Kanhere University of New South Wales
Guodong Long
Guodong Long University of Technology Sydney
Tao Gu
Tao Gu Macquarie University
Luiz Belardinelli
Luiz Belardinelli University of Florida
Zhiwen Yu
Zhiwen Yu Northwestern Polytechnical University
Liming Zhu
Liming Zhu Commonwealth Scientific and Industrial Research Organisation

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