Scholar
Yulun Zhang
Google Scholar ID: ORmLjWoAAAAJ
Associate Professor, Shanghai Jiao Tong University
Citations & Impact
Citations
27,917
H-index
61
i10-index
113
Publications
20
Co-authors
29
list available
Contact
Publications
Resume (English only)
Academic Achievements
- - Served as an Area Chair for CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, ACM MM, IJCAI, AAAI, WACV, PRCV, and Senior Program Committee (SPC) member for IJCAI, AAAI
- - Multiple papers accepted to ICCV 2025, ICML 2025, NeurIPS 2024, etc.
- - Received research funding from Adobe Research
- - Released projects such as DPoser, PromptSR, BiDRN, DeqIR, Reti-Diff
Research Experience
- - Tenure-track associate professor at School of Computer Science, Shanghai Jiao Tong University, since Mar. 2024
- - Postdoctoral researcher at Computer Vision Lab, ETH Zürich, Switzerland
- - Intern or visiting student at Adobe Research, Harvard University, Nanyang Technological University, The University of Sydney, and Shenzhen Institute of Advanced Technology, CAS
Education
- - Associate Professor at Shanghai Jiao Tong University, since Mar. 2024
- - Postdoctoral researcher at Computer Vision Lab, ETH Zürich, Switzerland
- - Ph.D. from Department of Electrical & Computer Engineering, Northeastern University, USA, in Aug. 2021
- - Master's degree from the Department of Automation, Tsinghua University, China, in Jul. 2017
- - B.E. degree from School of Electronic Engineering, Xidian University, China, in Jul. 2013
- - Intern or visiting student at Adobe Research, Harvard University, Nanyang Technological University, The University of Sydney, and Shenzhen Institute of Advanced Technology, CAS
Background
- Research interests include machine learning and computer vision. Specific areas of focus are image/video restoration (e.g., super-resolution, denoising, deblurring), synthesis (e.g., style transfer, texture transfer), biomedical image enhancement and analysis, deep model compression (e.g., network pruning, quantization), computational imaging (e.g., spectral compressive imaging), multimodal learning, large language models, and efficient diffusion models.
Miscellany
- Welcoming self-motivated undergraduate interns, graduate students, and PostDocs to join the group for impactful research. Interested candidates should email with their resume and transcript.
