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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
21204
World Ranking
1288
National Ranking
43

Jonathan Li 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 Jonathan Li 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: 513 publications — 94th percentile

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

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

Jonathan Li 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 Jonathan Li 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - IEEE Fellow for contributions to point cloud analytics in LiDAR remote sensing
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Fellow of the Engineering Institute of Canada
  • 2022 - Fellow of the Canadian Academy of Engineering
  • 2022 - Fellow of the Asia-Pacific Artificial Intelligence Association
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Jonathan Li is a researcher affiliated with the University of Waterloo in Canada. Their work spans multiple fields, with a focus on engineering, environmental science, and computer science. They have contributed extensively to subfields such as environmental engineering, computer vision and pattern recognition, geology, computational mechanics, and media technology.

Li's research covers a range of topics, particularly centered on remote sensing and LiDAR applications. Other main research themes include 3D surveying and cultural heritage, 3D shape modeling and analysis, automated road and building extraction, advanced neural network applications, remote-sensing image classification, and remote sensing in agriculture.

The scientist has published frequently in several venues, including:

  • International Journal of Applied Earth Observation and Geoinformation
  • arXiv (Cornell University)
  • IEEE Transactions on Geoscience and Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • IEEE Transactions on Intelligent Transportation Systems

Some recent papers authored or co-authored by Li include:

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review (2020), published in IEEE Transactions on Neural Networks and Learning Systems
  • Review: Deep Learning on 3D Point Clouds (2020), published in Remote Sensing
  • A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices (2020), published in Computers and Electronics in Agriculture
  • The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management (2022), published in Communications Earth & Environment
  • The Segment Anything Model (SAM) for remote sensing applications: From zero to one shot (2023), published in International Journal of Applied Earth Observation and Geoinformation

Jonathan Li collaborates frequently with several researchers, including José Marcato, Cheng Wang, Lingfei Ma, Wesley Nunes Gonçalves, and Kyle Gao. Their collaborative efforts have resulted in numerous publications.

Best Publications

  • Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

    Zilong Zhong;Jonathan Li;Zhiming Luo;Michael Chapman

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

  • A Review on Deep Learning in UAV Remote Sensing

    Lucas Prado Osco;José Marcato Junior;Ana Paula Marques Ramos;Lúcio André de Castro Jorge

  • Review: deep learning on 3D point clouds

    Saifullahi Aminu Bello;Shangshu Yu;Cheng Wang;Jibril Muhmmad Adam

  • Squeeze-and-Attention Networks for Semantic Segmentation

    Zilong Zhong;Zhong Qiu Lin;Rene Bidart;Xiaodan Hu

  • A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution

    Simon Wu;Jonathan Li;G.H. Huang

  • Using mobile laser scanning data for automated extraction of road markings

    Haiyan Guan;Jonathan Li;Jonathan Li;Yongtao Yu;Cheng Wang

  • Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds

    Bisheng Yang;Lina Fang;Jonathan Li

  • Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways

    Weikai Tan;Nannan Qin;Lingfei Ma;Ying Li

  • A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices

    Ana Paula Marques Ramos;Lucas Prado Osco;Danielle Elis Garcia Furuya;Wesley Nunes Gonçalves

  • Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data

    Xianfeng Zhang;Chunhua Liao;Jonathan Li;Quan Sun

  • Use of mobile LiDAR in road information inventory: a review

    Haiyan Guan;Jonathan Li;Shuang Cao;Yongtao Yu

  • LO-Net: Deep Real-Time Lidar Odometry

    Qing Li;Shaoyang Chen;Cheng Wang;Xin Li

  • Mobile Laser Scanned Point-Clouds for Road Object Detection and Extraction: A Review

    Lingfei Ma;Ying Li;Jonathan Li;Cheng Wang

  • Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A Factorized Architecture Search Framework

    Zilong Zhong;Ying Li;Lingfei Ma;Jonathan Li

  • Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang

  • Integration of orthoimagery and lidar data for object-based urban thematic mapping using random forests

    Haiyan Guan;Jonathan Li;Michael Chapman;Fei Deng

  • Fully convolutional networks for building and road extraction: Preliminary results

    Zilong Zhong;Jonathan Li;Weihong Cui;Han Jiang

  • Deep learning-based tree classification using mobile LiDAR data

    Haiyan Guan;Yongtao Yu;Zheng Ji;Jonathan Li

  • A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery

    Lucas Prado Osco;Mauro dos Santos de Arruda;José Marcato Junior;Neemias Buceli da Silva

  • Automated Extraction of Road Markings from Mobile Lidar Point Clouds

    Bisheng Yang;Lina Fang;Qingquan Li;Jonathan Li

  • Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Fukai Jia

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

Frequent Co-Authors

Chenglu Wen
Chenglu Wen Xiamen University
Yongtao Yu
Yongtao Yu Huaiyin Institute of Technology
Yulan Guo
Yulan Guo Sun Yat-sen University
Jun Yu
Jun Yu Hangzhou Dianzi University
Bisheng Yang
Bisheng Yang Wuhan University
Guohe Huang
Guohe Huang University of Regina
Qingquan Li
Qingquan Li Shenzhen University
Alexander Wong
Alexander Wong University of Waterloo
Sisi Zlatanova
Sisi Zlatanova University of New South Wales
Dongpu Cao
Dongpu Cao University of Waterloo

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