World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
10635
World Ranking
4359
National Ranking
581

Ligang 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 Ligang 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: 257 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Ligang 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 Ligang 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Ligang Liu is affiliated with the University of Science and Technology of China in China. Their research spans multiple disciplines, with a primary focus on engineering and computer science. This work encompasses a substantial body of publications emphasizing computational mechanics, computer vision and pattern recognition, as well as computer graphics and computer-aided design.

The scientist's prominent subfields of study include:

  • Computational Mechanics
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design
  • Mechanical Engineering
  • Aerospace Engineering

Their research covers several main topics, reflecting the breadth and depth of their academic contributions:

  • 3D Shape Modeling and Analysis
  • Advanced Numerical Analysis Techniques
  • Computer Graphics and Visualization Techniques
  • Advanced Vision and Imaging
  • Computational Geometry and Mesh Generation
  • 3D Surveying and Cultural Heritage
  • Robotics and Sensor-Based Localization

Ligang Liu has published extensively in notable venues, with frequent contributions to:

  • ACM Transactions on Graphics
  • arXiv (Cornell University)
  • Computer Graphics Forum
  • IEEE Transactions on Visualization and Computer Graphics
  • Computers & Graphics

Their collaborative work involves several frequent co-authors, indicating ongoing research partnerships. Key collaborators include:

  • Xiao-Ming Fu
  • Qing Fang
  • Renjie Chen
  • Xiaoya Zhai
  • Chunyang Ye

Among recent publications, these papers illustrate their research scope:

  • "HeadNeRF: A Realtime NeRF-based Parametric Head Model," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Efficient Representation and Optimization of TPMS-Based Porous Structures for 3D Heat Dissipation," 2021, Computer-Aided Design
  • "The Impact of the Wellness Tourism Experience on Tourist Well-Being: The Mediating Role of Tourist Satisfaction," 2023, Sustainability
  • "Easy2Hard: Learning to Solve the Intractables From a Synthetic Dataset for Structure-Preserving Image Smoothing," 2021, IEEE Transactions on Neural Networks and Learning Systems
  • "Efficient bijective parameterizations," 2020, ACM Transactions on Graphics

In addition to articles, Ligang Liu has contributed to book publications, including the recent title:

  • Addictive behaviors among youth and adolescents in the digital age, published in 2024 by Frontiers Media

Best Publications

  • Scanning 3D Full Human Bodies Using Kinects

    Jing Tong;Jin Zhou;Ligang Liu;Zhigeng Pan

  • A local/global approach to mesh parameterization

    Ligang Liu;Lei Zhang;Yin Xu;Craig Gotsman

  • Synthesis of bidirectional texture functions on arbitrary surfaces

    Xin Tong;Jingdan Zhang;Ligang Liu;Xi Wang

  • Optimizing Photo Composition

    Ligang Liu;Renjie Chen;Lior Wolf;Daniel Cohen-Or

  • Cost-effective printing of 3D objects with skin-frame structures

    Weiming Wang;Tuanfeng Y. Wang;Zhouwang Yang;Ligang Liu

  • HeadNeRF: A Realtime NeRF-based Parametric Head Model

    Unknown

  • Data-driven interior plan generation for residential buildings

    Wenming Wu;Xiao-Ming Fu;Rui Tang;Yuhan Wang

  • Parametric reshaping of human bodies in images

    Shizhe Zhou;Hongbo Fu;Ligang Liu;Daniel Cohen-Or

  • Guided Mesh Normal Filtering

    Wangyu Zhang;Bailin Deng;Bailin Deng;Juyong Zhang;Sofien Bouaziz

  • Co-Segmentation of 3D Shapes via Subspace Clustering

    Ruizhen Hu;Lubin Fan;Ligang Liu

  • FPConv: Learning Local Flattening for Point Convolution

    Yiqun Lin;Zizheng Yan;Haibin Huang;Dong Du

  • Easy Mesh Cutting

    Zhongping Ji;Ligang Liu;Zhonggui Chen;Guojin Wang

  • Semantic decomposition and reconstruction of residential scenes from LiDAR data

    Hui Lin;Jizhou Gao;Yu Zhou;Guiliang Lu

  • 3D Face Reconstruction With Geometry Details From a Single Image

    Luo Jiang;Juyong Zhang;Bailin Deng;Hao Li

  • Symmetry Hierarchy of Man‐Made Objects

    Yanzhen Wang;Yanzhen Wang;Kai Xu;Kai Xu;Jun Li;Hao Zhang

  • BCNet: Learning Body and Cloth Shape from A Single Image

    Boyi Jiang;Juyong Zhang;Yang Hong;Jinhao Luo

  • Partial intrinsic reflectional symmetry of 3D shapes

    Kai Xu;Hao Zhang;Andrea Tagliasacchi;Ligang Liu

  • Dual Laplacian editing for meshes

    O.K.-C. Au;C.L. Tai;L. Liu;H. Fu

  • Printing 3D objects with interlocking parts

    Peng Song;Zhongqi Fu;Ligang Liu;Chi-Wing Fu

  • Photo-inspired model-driven 3D object modeling

    Kai Xu;Hanlin Zheng;Hao Zhang;Daniel Cohen-Or

  • Decoupling noise and features via weighted ℓ1-analysis compressed sensing

    Ruimin Wang;Zhouwang Yang;Ligang Liu;Jiansong Deng

  • Saliency-Preserving Slicing Optimization for Effective 3D Printing

    Weiming Wang;Haiyuan Chao;Jing Tong;Zhouwang Yang

Frequent Co-Authors

Juyong Zhang
Juyong Zhang University of Science and Technology of China
Kai Xu
Kai Xu National University of Defense Technology
Xiaoguang Han
Xiaoguang Han Chinese University of Hong Kong
Craig Gotsman
Craig Gotsman New Jersey Institute of Technology
Falai Chen
Falai Chen University of Science and Technology of China
Hao Zhang
Hao Zhang Simon Fraser University
Baining Guo
Baining Guo Microsoft (United States)
Shuguang Cui
Shuguang Cui Chinese University of Hong Kong, Shenzhen
Heung-Yeung Shum
Heung-Yeung Shum Microsoft (United States)
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education can open doors to many high-demand tech careers. For students interested in engineering, pursuing an online electrical engineering degree ranking offers a look at top programs available across the USA. These flexible programs prepare graduates for evolving roles in the technology sector.

Some may prefer faster options. Choosing from the fastest masters degree online allows students to earn qualifications in less time, advancing careers swiftly. Others can benefit from earning quick certifications that pay well, which can be a practical, cost-effective way to upskill and boost employability.

For those wondering about long-term prospects, it’s useful to consider which master's degree is most in demand in usa. This can help guide your educational choices and align your studies with the current needs of the job market, maximizing opportunities after graduation.

Best Scientists Citing Ligang Liu

Trending Scientists

Recently Published Articles