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Rising Stars
2025

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Rising Stars 39 704 704 110 110 91 4107
Computer Science 35 11815 11479 4825 4617 105 4244

Zhizhong Han publications per year

The chart shows the history of publications by Zhizhong Han between 2004 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Zhizhong Han published across 22 years, from 2004 to 2025, averaging 5.4 papers a year. Output peaked at 26 publications in 2019. 19 of the 119 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 2004 to 2025. Vertical axis: number of publications, 0 to 26. Peak 26 publications in 2019. 2004: 1 publication 2005: 0 publications 2006: 0 publications 2007: 0 publications 2008: 0 publications 2009: 0 publications 2010: 1 publication 2011: 2 publications 2012: 1 publication 2013: 1 publication 2014: 0 publications 2015: 2 publications 2016: 2 publications 2017: 3 publications 2018: 4 publications 2019: 26 publications 2020: 17 publications 2021: 15 publications 2022: 7 publications 2023: 18 publications 2024: 11 publications 2025: 8 publications
2004 2025

119 publications in total across all disciplines

View publications per year as a table
Zhizhong Han: publications per year, 2004 to 2025
Year Publications
2004 1
2005 0
2006 0
2007 0
2008 0
2009 0
2010 1
2011 2
2012 1
2013 1
2014 0
2015 2
2016 2
2017 3
2018 4
2019 26
2020 17
2021 15
2022 7
2023 18
2024 11
2025 8
Total 119
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Zhizhong Han 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 Zhizhong Han sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 102–111 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 105 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420 105
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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Zhizhong Han 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 Zhizhong Han sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 34–35 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918 35
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Zhizhong Han is affiliated with Wayne State University in the United States and has contributed extensively to several areas within computer science and engineering, particularly focusing on 3D shape modeling and analysis, computer graphics, and computer vision. Their research spans diverse topics such as advanced vision and imaging, image processing and 3D reconstruction, advanced numerical analysis techniques, and medical image segmentation techniques.

The scientist's work is distributed across prominent publication venues, including:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Image Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence

Zhizhong Han's research output includes a strong presence in computational mechanics, computer vision and pattern recognition, computer graphics and computer-aided design, geology, and artificial intelligence. These subfields indicate a multidisciplinary approach to modeling and reconstructing 3D data and advanced analytical techniques.

Notable recent papers authored by Zhizhong Han include:

  • SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction With Self-Projection Optimization, 2022, IEEE Transactions on Image Processing
  • Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Surface Reconstruction from Point Clouds by Learning Predictive Context Priors, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Frequent coauthors collaborating with Zhizhong Han reflect a network of research relationships contributing to the advancement of 3D shape and image processing fields. These include:

  • Yu-Shen Liu
  • Matthias Zwicker
  • Xin Wen
  • Baorui Ma
  • Yan-Pei Cao

Best Publications

  • Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network

    Xinhai Liu;Zhizhong Han;Yu-Shen Liu;Matthias Zwicker

  • SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

    Peng Xiang;Xin Wen;Yu-Shen Liu;Yan-Pei Cao

  • Point Cloud Completion by Skip-Attention Network With Hierarchical Folding

    Xin Wen;Tianyang Li;Zhizhong Han;Yu-Shen Liu

  • SeqViews2SeqLabels: Learning 3D Global Features via Aggregating Sequential Views by RNN With Attention

    Zhizhong Han;Mingyang Shang;Zhenbao Liu;Chi-Man Vong

  • SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization

    Yue Jiang;Dantong Ji;Zhizhong Han;Matthias Zwicker

  • PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths

    Xin Wen;Peng Xiang;Zhizhong Han;Yan-Pei Cao

  • 3D2SeqViews: Aggregating Sequential Views for 3D Global Feature Learning by CNN With Hierarchical Attention Aggregation

    Zhizhong Han;Honglei Lu;Zhenbao Liu;Chi-Man Vong

  • Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds From Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction

    Zhizhong Han;Xiyang Wang;Yu-Shen Liu;Matthias Zwicker

  • View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions

    Zhizhong Han;Mingyang Shang;Yu-Shen Liu;Matthias Zwicker

  • Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding

    Xin Wen;Zhizhong Han;Yan-Pei Cao;Pengfei Wan

  • Surface Reconstruction from Point Clouds by Learning Predictive Context Priors

    Unknown

  • Reconstructing Surfaces for Sparse Point Clouds with On-Surface Priors

    Unknown

  • Snowflake Point Deconvolution for Point Cloud Completion and Generation With Skip-Transformer

    Unknown

  • L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention

    Xinhai Liu;Zhizhong Han;Xin Wen;Yu-Shen Liu

  • Learning Deep Implicit Functions for 3D Shapes with Dynamic Code Clouds

    Unknown

  • SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization.

    Xinhai Liu;Xinchen Liu;Zhizhong Han;Yu-Shen Liu

  • 3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow

    Unknown

  • Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences

    Zhizhong Han;Mingyang Shang;Xiyang Wang;Yu-Shen Liu

  • Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network With Coupled Softmax

    Zhizhong Han;Zhenbao Liu;Chi-Man Vong;Yu-Shen Liu

  • Unsupervised 3D Local Feature Learning by Circle Convolutional Restricted Boltzmann Machine

    Zhizhong Han;Zhenbao Liu;Junwei Han;Chi-Man Vong

  • 3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention

    Zhizhong Han;Zhizhong Han;Xiyang Wang;Chi Man Vong;Yu-Shen Liu

  • Mesh Convolutional Restricted Boltzmann Machines for Unsupervised Learning of Features With Structure Preservation on 3-D Meshes

    Zhizhong Han;Zhenbao Liu;Junwei Han;Chi-Man Vong

  • Render4Completion: Synthesizing Multi-View Depth Maps for 3D Shape Completion

    Tao Hu;Zhizhong Han;Abhinav Shrivastava;Matthias Zwicker

  • DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images

    Zhizhong Han;Chao Chen;Yu-Shen Liu;Matthias Zwicker

  • Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces

    Baorui Ma;Zhizhong Han;Yu-Shen Liu;Matthias Zwicker

Frequent Co-Authors

Matthias Zwicker
Matthias Zwicker University of Maryland, College Park
Chi-Man Vong
Chi-Man Vong University of Macau
Junwei Han
Junwei Han Northwestern Polytechnical University
C. L. Philip Chen
C. L. Philip Chen South China University of Technology
Shuhui Bu
Shuhui Bu Northwestern Polytechnical University
Yu-Kun Lai
Yu-Kun Lai Cardiff University
Abhinav Shrivastava
Abhinav Shrivastava University of Maryland, College Park
Yi Chang
Yi Chang Jilin University
Xuelong Li
Xuelong Li China Telecom (China)
Ralph R. Martin
Ralph R. Martin Cardiff University

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