2026 Jun-Yan Zhu: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Rising Stars	60	157	157	19	19	92	65714
Computer Science	62	2817	2734	1391	1340	150	51278

Research.com Recognitions

2025 - Research.com Rising Stars Award

Overview

Jun-Yan Zhu is a researcher affiliated with Carnegie Mellon University in the United States. The primary area of their research is Computer Science, with a strong focus on Computer Vision and Pattern Recognition, accounting for the majority of their publications. Other subfields of study include Artificial Intelligence, Computer Graphics and Computer-Aided Design, Computational Mechanics, and Human-Computer Interaction.

Their work extensively covers key topics such as Generative Adversarial Networks and Image Synthesis, Advanced Vision and Imaging, Computer Graphics and Visualization Techniques, Advanced Image and Video Retrieval Techniques, Advanced Image Processing Techniques, 3D Shape Modeling and Analysis, and Video Analysis and Summarization.

Frequent venues for their research outputs include arXiv (Cornell University), where they have published over 50 papers, as well as the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) with six publications. Other frequent publication venues are Lecture Notes in Computer Science, the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), and ACM Transactions on Graphics.

Jun-Yan Zhu has collaborated with several co-authors, notably:

Richard Zhang (26 joint publications)
Eli Shechtman (14 joint publications)
Antonio Torralba (13 joint publications)
Alexei A. Efros (12 joint publications)
Taesung Park (11 joint publications)

Representative recent papers include:

"Depth-supervised NeRF: Fewer Views and Faster Training for Free," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
"Understanding the role of individual units in a deep neural network," 2020, Proceedings of the National Academy of Sciences
"SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations," 2021, arXiv (Cornell University)
"On Aliased Resizing and Surprising Subtleties in GAN Evaluation," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
"Dataset Distillation by Matching Training Trajectories," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Best Publications

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks

Jun-Yan Zhu;Taesung Park;Phillip Isola;Alexei A. Efros

22900
Citations
Image-to-Image Translation with Conditional Adversarial Networks

Phillip Isola;Jun-Yan Zhu;Tinghui Zhou;Alexei A. Efros

20939
Citations
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

Ting-Chun Wang;Ming-Yu Liu;Jun-Yan Zhu;Andrew Tao

4514
Citations
Semantic Image Synthesis With Spatially-Adaptive Normalization

Taesung Park;Ming-Yu Liu;Ting-Chun Wang;Jun-Yan Zhu

2890
Citations
CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Judy Hoffman;Eric Tzeng;Taesung Park;Jun-Yan Zhu

2452
Citations
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

Jun-Yan Zhu;Taesung Park;Phillip Isola;Alexei A. Efros

2128
Citations
Image-to-Image Translation with Conditional Adversarial Networks

Phillip Isola;Jun-Yan Zhu;Tinghui Zhou;Alexei A. Efros

1397
Citations
Generative Visual Manipulation on the Natural Image Manifold

Jun-Yan Zhu;Philipp Krähenbühl;Eli Shechtman;Alexei A. Efros

1361
Citations
Contrastive Learning for Unpaired Image-to-Image Translation

Taesung Park;Alexei A. Efros;Richard Zhang;Jun Yan Zhu

1321
Citations
Depth-supervised NeRF: Fewer Views and Faster Training for Free

Unknown

1139
Citations
Learning the signatures of the human grasp using a scalable tactile glove.

Subramanian Sundaram;Petr Kellnhofer;Yunzhu Li;Jun-Yan Zhu

1059
Citations
Toward Multimodal Image-to-Image Translation

Jun Yan Zhu;Richard Zhang;Deepak Pathak;Trevor Darrell

1044
Citations
Generating Adversarial Examples with Adversarial Networks

Chaowei Xiao;Bo Li;Jun-yan Zhu;Jun-yan Zhu;Warren He

888
Citations
Multimodal Image-to-Image Translation by Enforcing Bi-Cycle Consistency

Jun-Yan Zhu;Richard Zhang;Deepak Pathak;Trevor Darrell

846
Citations
Multi-Concept Customization of Text-to-Image Diffusion

Unknown

721
Citations
Real-time user-guided image colorization with learned deep priors

Richard Zhang;Jun-Yan Zhu;Phillip Isola;Xinyang Geng

633
Citations
Video-to-Video Synthesis

Ting-Chun Wang;Ming-Yu Liu;Jun-Yan Zhu;Guilin Liu

585
Citations
Toward Multimodal Image-to-Image Translation

Jun-Yan Zhu;Richard Zhang;Deepak Pathak;Trevor Darrell

485
Citations
Scaling up GANs for Text-to-Image Synthesis

Unknown

466
Citations
CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Judy Hoffman;Eric Tzeng;Taesung Park;Jun-Yan Zhu

461
Citations
Semantic photo manipulation with a generative image prior

David Bau;Hendrik Strobelt;William Peebles;Jonas Wulff

426
Citations
Zero-shot Image-to-Image Translation

Unknown

417
Citations
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

David Bau;Jun-Yan Zhu;Hendrik Strobelt;Bolei Zhou

409
Citations
Differentiable Augmentation for Data-Efficient GAN Training

Shengyu Zhao;Zhijian Liu;Ji Lin;Jun-Yan Zhu

403
Citations
On Aliased Resizing and Surprising Subtleties in GAN Evaluation

Unknown

389
Citations
Understanding the role of individual units in a deep neural network.

David Bau;Jun-Yan Zhu;Hendrik Strobelt;Agata Lapedriza

367
Citations
State of the Art on Neural Rendering

Ayush Tewari;Ohad Fried;Justus Thies;Vincent Sitzmann

366
Citations
Spatially transformed adversarial examples

Chaowei Xiao;Jun Yan Zhu;Bo Li;Warren He

352
Citations
Dataset Distillation by Matching Training Trajectories

Unknown

328
Citations
Advances in neural rendering

A. Tewari;O. Fried;J. Thies;V. Sitzmann

62
Citations

Frequent Co-Authors

Alexei A. Efros University of California, Berkeley

Antonio Torralba MIT

David Bau Northeastern University

Eli Shechtman Adobe Systems (United States)

Jiajun Wu Stanford University

Phillip Isola MIT

Joshua B. Tenenbaum MIT

Bolei Zhou University of California, Los Angeles

Hendrik Strobelt IBM (United States)

Zhuowen Tu University of California, San Diego

External Links

Personal website of Jun-Yan Zhu Google Scholar page

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

Related Online Degrees & Career Pathways

As the demand for tech-savvy professionals grows, exploring related online degrees can broaden your career horizons beyond traditional computer science. Specialized programs such as an online masters in data science provide a deep dive into data analytics, machine learning, and AI—skills highly valued across industries.

For those interested in bridging technology with real-world projects, an online building construction degree can lead to roles in construction tech, project management, and sustainable design. Pursuing an mba online cheap is also a smart choice for computer science graduates aiming to move into tech entrepreneurship or leadership roles without committing to years of study.

Additionally, online masters options let students rapidly upskill or switch fields, accelerating entry into emerging digital careers. These flexible online pathways provide affordable, accessible options for advancing your education and expanding your professional future.