I am a third-year PhD student (2023-) in the Department of Computer Science at University of Illinois at Chicago (UIC), supervised by Prof. Yan Yan. Prior to joining UIC, I spent a year at Illinois Institute of Technology. I hold both a bachelor’s and a master’s degree from Shanghai Jiao Tong University, where I was fortune to be advised by Prof. Junchi Yan. Additionally, I had a wonderful time working as a research intern with Prof. Anqi Liu and Prof. Anima Anandkumar at Caltech.

My research interests include Machine Learning Efficiency, 3D Vision and Robotics. Most of the publications can be accessed here.

🔥 News

  • 2025.09:   3 co-authored papers accepted to NeurIPS 2025
  • 2025.06:   2 papers accepted to ICCV 2025
  • 2025.05:   Working as a research intern at Cisco Research
  • 2025.03:   1 paper accepted to CVPR 2025
  • 2024.11:   Serving as the web co-chair for ICMR 2025
  • 2024.06:   1 paper accepted to NeurIPS 2024

📝 Selected Publications

ICCV 2025
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QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Haoxuan Wang, Yuzhang Shang, Zhihang Yuan, Junyi Wu, Junchi Yan, Yan Yan

Code GitHub Repo stars

  • Parameter efficient finetuning method for diffusion model quantization.
ICCV 2025
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CaO$_2$: Rectifying Inconsistencies in Diffusion-Based Dataset Distillation

Haoxuan Wang, Zhenghao Zhao, Junyi Wu, Yuzhang Shang, Gaowen Liu, Yan Yan

Code GitHub Repo stars

  • Diffusion based method for efficient dataset distillation.
CVPR 2025
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Distilling Long-tailed Datasets

Zhenghao Zhao*, Haoxuan Wang*, Yuzhang Shang, Kai Wang, Yan Yan

Code GitHub Repo stars

  • Pioneering work confronting biased dataset distillation.
NeurIPS 2024
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PTQ4DiT: Post-training Quantization for Diffusion Transformers

Junyi Wu*, Haoxuan Wang*, Yuzhang Shang, Mubarak Shah, Yan Yan

Code GitHub Repo stars

  • Pioneering work for DiT quantization.
IJCAI 2023
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Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach

Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu and Junchi Yan

Project

  • A novel framework for learning calibrated uncertainties under domain shifts.

[NeurIPS 2025 (spotlight)] X-Field: A Physically Grounded Representation for 3D X-ray Reconstruction, Feiran Wang*, Jiachen Tao*, Junyi Wu*, Haoxuan Wang, Bin Duan, Kai Wang, Zongxin Yang, Yan Yan

[NeurIPS 2025] Efficient Multimodal Dataset Distillation via Generative Models, Zhenghao Zhao, Haoxuan Wang, Junyi Wu, Yuzhang Shang, Gaowen Liu, Yan Yan

[NeurIPS 2025] Orientation-anchored Hyper-Gaussian for 4D Reconstruction from Casual Videos Junyi Wu, Jiachen Tao, Haoxuan Wang, Gaowen Liu, Ramana Rao Kompella, Yan Yan

Leveraging Angular Information Between Feature and Classifier for Long-tailed Learning: A Prediction Reformulation Approach, Haoxuan Wang, Junchi Yan

🎖 Honors and Awards

  • 2021-22 First Award of SJTU scholarship
  • 2020.06 Graduation with honor, University Graduate Excellence Award of SJTU
  • 2019.11 First Award of Zhiyuan Research Program

📖 Educations

  • 2024.12 - current  PhD, University of Illinois at Chicago.
  • 2023.09 - 2024.12  PhD, Illinois Institute of Technology.
  • 2020.09 - 2023.03  Master, Shanghai Jiao Tong University.
  • 2016.09 - 2020.06  Undergraduate, IEEE Honor Class, Shanghai Jiao Tong University.