World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6865
World Ranking
8861
National Ranking
351

Renjie Liao 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 Renjie Liao 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: 90 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Renjie Liao 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 Renjie Liao 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Renjie Liao is affiliated with the University of British Columbia in Canada. Their research primarily spans the fields of Computer Science and Engineering, with publications notably focused on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Cardiology and Cardiovascular Medicine, and Computational Mechanics.

Their work broadly covers multiple research topics including Autonomous Vehicle Technology and Safety, Anomaly Detection Techniques and Applications, Domain Adaptation and Few-Shot Learning, Video Surveillance and Tracking Methods, Multimodal Machine Learning Applications, 3D Shape Modeling and Analysis, and Advanced Neural Network Applications.

Some recent papers authored or co-authored by Renjie Liao include:

  • LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting, 2021, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Structure-Coherent Deep Feature Learning for Robust Face Alignment, 2021, IEEE Transactions on Image Processing
  • Learning Lane Graph Representations for Motion Forecasting, 2020, arXiv (Cornell University)

Renjie Liao frequently collaborates with a group of co-authors, including Raquel Urtasun, Ming Liang, Leonid Sigal, Teresa S.M. Tsang, and Purang Abolmaesumi.

Their publications appear regularly in several venues, with the most frequent being arXiv (Cornell University), where they have contributed 40 papers. Other notable publication venues include the 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Lecture Notes in Computer Science, and the 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

Best Publications

  • Learning Lane Graph Representations for Motion Forecasting

    Ming Liang;Bin Yang;Rui Hu;Yun Chen

  • Detail-Revealing Deep Video Super-Resolution

    Xin Tao;Hongyun Gao;Renjie Liao;Jue Wang

  • 3D Graph Neural Networks for RGBD Semantic Segmentation

    Xiaojuan Qi;Renjie Liao;Jiaya Jia;Sanja Fidler

  • UPSNet: A Unified Panoptic Segmentation Network

    Yuwen Xiong;Renjie Liao;Hengshuang Zhao;Rui Hu

  • GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation

    Xiaojuan Qi;Renjie Liao;Zhengzhe Liu;Raquel Urtasun

  • Video Super-Resolution via Deep Draft-Ensemble Learning

    Renjie Liao;Xin Tao;Ruiyu Li;Ziyang Ma

  • Deep Edge-Aware Filters

    Li Xu;Jimmy Ren;Qiong Yan;Renjie Liao

  • Efficient Graph Generation with Graph Recurrent Attention Networks

    Renjie Liao;Renjie Liao;Yujia Li;Yang Song;Shenlong Wang;Shenlong Wang

  • LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting.

    Wenyuan Zeng;Ming Liang;Renjie Liao;Raquel Urtasun

  • LanczosNet: Multi-Scale Deep Graph Convolutional Networks

    Renjie Liao;Renjie Liao;Zhizhen Zhao;Raquel Urtasun;Raquel Urtasun;Richard S. Zemel;Richard S. Zemel

  • SpAGNN: Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data

    Sergio Casas;Cole Gulino;Renjie Liao;Raquel Urtasun

  • NerveNet: Learning Structured Policy with Graph Neural Networks

    Tingwu Wang;Renjie Liao;Jimmy Ba;Sanja Fidler

  • Learning to generate images with perceptual similarity metrics

    Jake Snell;Karl Ridgeway;Renjie Liao;Brett D. Roads

  • Handling motion blur in multi-frame super-resolution

    Ziyang Ma;Renjie Liao;Xin Tao;Li Xu

  • Learning Deep Structured Active Contours End-to-End

    Lisa Zhang;Min Bai;Renjie Liao;Raquel Urtasun

  • Learning Important Spatial Pooling Regions for Scene Classification

    Di Lin;Cewu Lu;Renjie Liao;Jiaya Jia

  • Situation Recognition with Graph Neural Networks

    Ruiyu Li;Makarand Tapaswi;Renjie Liao;Jiaya Jia

  • DARNet: Deep Active Ray Network for Building Segmentation

    Dominic Cheng;Renjie Liao;Sanja Fidler;Raquel Urtasun

  • Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

    Sergio Casas;Cole Gulino;Simon Suo;Katie Luo

  • LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving

    Alexander Cui;Sergio Casas;Abbas Sadat;Renjie Liao

  • Understanding Short-Horizon Bias in Stochastic Meta-Optimization

    Yuhuai Wu;Mengye Ren;Renjie Liao;Roger B. Grosse

  • Efficient Graph Generation with Graph Recurrent Attention Networks

    Renjie Liao;Yujia Li;Yang Song;Shenlong Wang

Frequent Co-Authors

Raquel Urtasun
Raquel Urtasun University of Toronto
Richard S. Zemel
Richard S. Zemel University of Toronto
Jiaya Jia
Jiaya Jia Hong Kong University of Science and Technology
Sanja Fidler
Sanja Fidler University of Toronto
Michael C. Mozer
Michael C. Mozer Google (United States)
Xiaojuan Qi
Xiaojuan Qi University of Hong Kong
Stefano Ermon
Stefano Ermon Stanford University
Jianping Shi
Jianping Shi SenseTime
David Duvenaud
David Duvenaud University of Toronto
Hengshuang Zhao
Hengshuang Zhao University of Hong Kong

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