2026 Leonidas J. Guibas: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	148	37	35	21	20	646	119991

Research.com Recognitions

2026 - Research.com Computer Science in United States Leader Award
2025 - Research.com Computer Science in United States Leader Award
2023 - Research.com Computer Science in United States Leader Award
2022 - Research.com Computer Science in United States Leader Award
2018 - Fellow of the American Academy of Arts and Sciences
2017 - Member of the National Academy of Engineering For contributions to data structures, algorithm analysis, and computational geometry.
2012 - IEEE Fellow For contributions to algorithms for computational geometry
2007 - ACM AAAI Allen Newell Award For pioneering work in computational geometry, with profound applications across an astonishingly broad range of Computer Science disciplines.
1999 - ACM Fellow For his work on geometric data structures, arrangements of surfaces and their applications, geometric algorithms in computer graphics, and algorithmic issues in computer vision.

Overview

Leonidas J. Guibas is affiliated with Stanford University in the United States. Their research primarily spans the fields of Computer Science and Engineering, with a notable focus on Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Control and Systems Engineering, and Artificial Intelligence.

The main topics covered in their work include 3D Shape Modeling and Analysis, Computer Graphics and Visualization Techniques, Advanced Vision and Imaging, Human Pose and Action Recognition, 3D Surveying and Cultural Heritage, Robotics and Sensor-Based Localization, and Image Processing and 3D Reconstruction.

Among their recent publications are the following papers:

ShapeNet: An Information-Rich 3D Model Repository, 2023, published in Zenodo (CERN European Organization for Nuclear Research)
Efficient Geometry-aware 3D Generative Adversarial Networks, 2022, published in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation, 2022, published in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Vector Neurons: A General Framework for SO(3)-Equivariant Networks, 2021, published in 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Next-generation deep learning based on simulators and synthetic data, 2021, published in Trends in Cognitive Sciences

Frequent collaborators in their research include Kaichun Mo, Tolga Birdal, Gordon Wetzstein, Congyue Deng, and Yanchao Yang.

Their work has been published predominantly in venues such as:

arXiv (Cornell University)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
ACM Transactions on Graphics
Computer Graphics Forum

Leonidas J. Guibas has received several professional honors, including:

Fellow of the American Academy of Arts and Sciences, 2018
Member of the National Academy of Engineering, 2017, for contributions to data structures, algorithm analysis, and computational geometry
IEEE Fellow, 2012, for contributions to algorithms for computational geometry
ACM AAAI Allen Newell Award, 2007, for pioneering work in computational geometry with applications across various Computer Science disciplines
ACM Fellow, 1999, for work on geometric data structures, arrangements of surfaces and applications, geometric algorithms in computer graphics, and algorithmic issues in computer vision

Best Publications

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

R. Qi Charles;Hao Su;Mo Kaichun;Leonidas J. Guibas

10699
Citations
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Charles Ruizhongtai Qi;Li Yi;Hao Su;Leonidas J. Guibas

8639
Citations
The Earth Mover's Distance as a Metric for Image Retrieval

Yossi Rubner;Carlo Tomasi;Leonidas J. Guibas

6347
Citations
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Charles R. Qi;Hao Su;Kaichun Mo;Leonidas J. Guibas

3097
Citations
KPConv: Flexible and Deformable Convolution for Point Clouds

Hugues Thomas;Charles R. Qi;Jean-Emmanuel Deschaud;Beatriz Marcotegui

2534
Citations
Frustum PointNets for 3D Object Detection from RGB-D Data

Charles R. Qi;Wei Liu;Chenxia Wu;Hao Su

2433
Citations
A Point Set Generation Network for 3D Object Reconstruction from a Single Image

Haoqiang Fan;Hao Su;Leonidas Guibas

2393
Citations
A metric for distributions with applications to image databases

Y. Rubner;C. Tomasi;L.J. Guibas

2327
Citations
ShapeNet: An Information-Rich 3D Model Repository

Angel X. Chang;Thomas A. Funkhouser;Leonidas J. Guibas;Pat Hanrahan

2234
Citations
Primitives for the manipulation of general subdivisions and the computation of Voronoi

Leonidas Guibas;Jorge Stolfi

2102
Citations
Wireless Sensor Networks: An Information Processing Approach

Feng Zhao;Leonidas Guibas

2020
Citations
A concise and provably informative multi-scale signature based on heat diffusion

Jian Sun;Maks Ovsjanikov;Leonidas Guibas

1827
Citations
Volumetric and Multi-view CNNs for Object Classification on 3D Data

Charles R. Qi;Hao Su;Matthias NieBner;Angela Dai

1677
Citations
A scalable active framework for region annotation in 3D shape collections

Li Yi;Vladimir G. Kim;Duygu Ceylan;I-Chao Shen

1206
Citations
Deep Hough Voting for 3D Object Detection in Point Clouds

Charles R. Qi;Or Litany;Kaiming He;Leonidas Guibas

1075
Citations
A dichromatic framework for balanced trees

Leo J. Guibas;Robert Sedgewick

1047
Citations
Locating and bypassing holes in sensor networks

Qing Fang;Jie Gao;Leonidas J. Guibas

935
Citations
Robust Monte Carlo methods for light transport simulation

Leonidas J. Guibas;Eric Veach

924
Citations
Learning Representations and Generative Models for 3D Point Clouds.

Panos Achlioptas;Olga Diamanti;Ioannis Mitliagkas;Leonidas J. Guibas

920
Citations
Taskonomy: Disentangling Task Transfer Learning

Amir R. Zamir;Alexander Sax;William Shen;Leonidas Guibas

900
Citations
Volumetric and Multi-View CNNs for Object Classification on 3D Data

Charles R. Qi;Hao Su;Matthias Niessner;Angela Dai

375
Citations
Deep Knowledge Tracing

Chris Piech;Jonathan Spencer;Jonathan Huang;Surya Ganguli

337
Citations
Taskonomy: Disentangling Task Transfer Learning.

Amir Roshan Zamir;Amir Roshan Zamir;Alexander Sax;William B. Shen;Leonidas J. Guibas

168
Citations
Primitives for the manipulation of general subdivisions and the computation of Voronoi diagrams

Leo J. Guibas;Jorge Stolfi

137
Citations

Frequent Co-Authors

Micha Sharir Tel Aviv University

Hao Su University of California, San Diego

John Hershberger Mentor Graphics

Qixing Huang The University of Texas at Austin

Herbert Edelsbrunner Institute of Science and Technology Austria

Maks Ovsjanikov École Polytechnique

Jie Gao Rutgers, The State University of New Jersey

Li Zhang Google (United States)

Bernard Chazelle Princeton University

Niloy J. Mitra University College London

External Links

Wikipedia of Leonidas J. Guibas Personal website of Leonidas J. Guibas Google Scholar page

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