World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6207
World Ranking
10709
National Ranking
4475

Jun 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 Jun 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: 85 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

Jun 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 Jun 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: 37 D-Index — 27th percentile

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

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

Overview

Jun Liu is affiliated with Infinia ML in the United States and works primarily within the field of Engineering. Their research contributions span a wide range of engineering disciplines, with a strong emphasis on Computational Mechanics and Aerospace Engineering.

The subfields in which they have published include:

  • Computational Mechanics
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Applied Mathematics

Their work covers several main topics including:

  • Computational Fluid Dynamics and Aerodynamics
  • Fluid Dynamics and Turbulent Flows
  • Gas Dynamics and Kinetic Theory
  • Rocket and propulsion systems research
  • Advanced Numerical Methods in Computational Mathematics
  • Advanced Aircraft Design and Technologies
  • Aerodynamics and Fluid Dynamics Research

Jun Liu has published in numerous venues, with frequent contributions to:

  • Aerospace Science and Technology
  • arXiv (Cornell University)
  • Chinese Journal of Aeronautics
  • Aerospace
  • Computers & Fluids

Notable recent papers authored or coauthored by Jun Liu include:

  • The role of energy storage systems in resilience enhancement of health care centers with critical loads, 2020, Journal of Energy Storage

Other significant publications in the extended dataset, while not authored by Jun Liu directly but appearing in the same research context, include:

  • Boundary-layer viscous correction method for hypersonic forebody/inlet integration, 2021, Acta Astronautica
  • Phase interface manipulation by adjusting atomic ordering in metal-organic framework to facilitate microwave absorption, 2023, Carbon
  • Hypersonic flow control of shock wave/turbulent boundary layer interactions using magnetohydrodynamic plasma actuators, 2020, Journal of Zhejiang University. Science A
  • Research status and development trend of air-breathing high-speed vehicle/engine integration, 2024, Aerospace Science and Technology

Frequent coauthors collaborating with Jun Liu include:

  • Huacheng Yuan
  • Shibin Luo
  • Yuhang Sun
  • Jiaqi Tian
  • Jiawen Song

Best Publications

  • Multi-task feature learning via efficient l 2, 1 -norm minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Face liveness detection from a single image with sparse low rank bilinear discriminative model

    Xiaoyang Tan;Yi Li;Jun Liu;Lin Jiang

  • SLEP: Sparse Learning with Efficient Projections

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Efficient Methods for Overlapping Group Lasso

    Lei Yuan;Jun Liu;Jieping Ye

  • A multi-task learning formulation for predicting disease progression

    Jiayu Zhou;Lei Yuan;Jun Liu;Jieping Ye

  • Making FLDA applicable to face recognition with one sample per person

    Songcan Chen;Jun Liu;Zhi-Hua Zhou

  • Modeling disease progression via multi-task learning

    Jiayu Zhou;Jun Liu;Vaibhav A. Narayan;Jieping Ye

  • Modeling disease progression via fused sparse group lasso

    Jiayu Zhou;Jun Liu;Vaibhav A. Narayan;Jieping Ye

  • Large-scale sparse logistic regression

    Jun Liu;Jianhui Chen;Jieping Ye

  • An efficient algorithm for a class of fused lasso problems

    Jun Liu;Lei Yuan;Jieping Ye

  • Moreau-Yosida Regularization for Grouped Tree Structure Learning

    Jun Liu;Jieping Ye

  • A convex formulation for learning shared structures from multiple tasks

    Jianhui Chen;Lei Tang;Jun Liu;Jieping Ye

  • Efficient Euclidean projections in linear time

    Jun Liu;Jieping Ye

  • Face Recognition Under Occlusions and Variant Expressions With Partial Similarity

    Xiaoyang Tan;Songcan Chen;Zhi-Hua Zhou;Jun Liu

  • Sparse methods for biomedical data

    Jieping Ye;Jun Liu

  • Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data

    Shuai Huang;Jing Li;Liang Sun;Jun Liu

  • Altered brain network modules induce helplessness in major depressive disorder

    Daihui Peng;Feng Shi;Ting Shen;Ziwen Peng

  • Semi-random subspace method for face recognition

    Yulian Zhu;Jun Liu;Songcan Chen

  • Sparse non-negative tensor factorization using columnwise coordinate descent

    Ji Liu;Jun Liu;Peter Wonka;Jieping Ye

  • Safe Screening with Variational Inequalities and Its Application to Lasso

    Jun Liu;Zheng Zhao;Jie Wang;Jieping Ye

  • A Safe Screening Rule for Sparse Logistic Regression

    Jie Wang;Jiayu Zhou;Jun Liu;Peter Wonka

  • Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images

    Kelei He;Wei Zhao;Xingzhi Xie;Wen Ji

Frequent Co-Authors

Jieping Ye
Jieping Ye Alibaba Group (China)
Songcan Chen
Songcan Chen Nanjing University of Aeronautics and Astronautics
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Dinggang Shen
Dinggang Shen ShanghaiTech University
Jiayu Zhou
Jiayu Zhou Michigan State University
Shuiwang Ji
Shuiwang Ji Texas A&M University
Feng Shi
Feng Shi United Imaging Intelligence (China)
Eric M. Reiman
Eric M. Reiman Arizona State University

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