Hi! I am Xiaohui Wang, a final-year undergraduate student majoring in Electronic Information Science and Technology at Fudan University. I am fortunate to be advised by Prof. Tao Chen at the Fudan EDL Lab. I also work closely with Dr. Peng Ye (Postdoc at MMLab@CUHK. My research interests lie in Efficient AI and Embodied AI.
I am proud to have received the National Scholarship twice (2022β2023, 2024β2025) for my academic achievements. I am passionate about exploring ways to enhance AI systems for more efficient and versatile real-world applications.
I have worked as a research intern at MMLab@HKU under the supervision of Prof. Ping Luo. I am excited to work alongside talented researchers.
In addition, I am a member of the EGA robotics team at Fudan University, representing the university in the RoboMaster competition.
In Fall 2026, I will be joining The Hong Kong University of Science and Technology (HKUST) as a Ph.D. student.
If you are interested in connecting, collaborating, or discussing ideas, feel free to reach out to me via email. You can also access my CV HERE.
π₯ News
- 2025.10: Β ππ I have received my second National Scholarship. Many thanks for the recognition!
- 2025.09: Β ππ Our work UltraDelta has been accepted as a poster at NeurIPS 2025οΌ
- 2025.05: Β ππ Our work UltraDelta is now on arxivοΌ
- 2025.05: Β ππ I am proud to be named one of the Top 10 Students in the School of Information Science and Technology!
- 2025.05: Β ππ I have received the Fumei Summer Research Scholarship. Many thanks to the Fumei Foundation!
- 2025.03: Β ππ Our work Delta-DCT is now on arxivοΌ
- 2023.12: Β ππ I have received the National Scholarship. Many thanks for the recognition!
π Honors and Awards
- 2024-2025 National Scholarship
- 2022-2023 National Scholarship
- 2024-2025 Top 10 Student Award at School of Information Science and Technology
- 2025.05 Fumei Summer Research Scholarship (awarded to only 4 students at Fudan University)
- 2023-2024 SCSK Corporation Scholarship
- 2024.09 China Undergraduate Mathematical Contest in Modeling (Second Prize, Shanghai)
π Publications
Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression
Xiaohui Wang*, Peng Ye*, Chenyu Huang, Shenghe Zheng, Bo Zhang, Lei Bai, Wanli Ouyang, Tao Chenβ
(Accepted by NeurIPS 2025)
- To break the compression ceiling of delta weights, we analyze the limitations of existing methods in information preservation and model stability, and propose UltraDelta, the first data-free pipeline enabling ultra-efficient delta compression, achieving both ultra-high compression ratios and strong performance without relying on any data.
Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform
Chenyu Huang*, Peng Ye*, Xiaohui Wang, Shenghe Zheng, Biqing Qi, Lei Bai, Wanli Ouyang, Tao Chenβ
- Motivated by the classic JPEG compression, we explore the delta compression from the DCT domain for the first time. We first realize data-free delta compression and further reduce the performance degradation. We propose a framework based on compression in the DCT domain, named DELTA-DCT.
π Education
- 2022.06 - present, Electronic Information Science and Technology, Fudan University. (GPA:93/100, rank: 5/95 in class, 5/206 in school)
- 2025.06 - 2025.09, School of Computing and Data Science, The University of Hong Kong (Summer Intern at MMLab@HKU)
Last update in October 2025