๐ About Me
I am currently a second-year Ph.D. in Electrical and Computer Engineering at the University of Arizona, advised by Dr. Huanrui Yang. Prior to joining UA, I earned my M.S. from University of Chinese Academy of Sciences in 2024 and my B.E. from Beijing Forestry University in 2021.
๐ My research focuses on AI Infra, with a focus on model quantization, KV cache optimization and token pruning.
๐ค Actively looking for 2027(Spring/Summer) internship opportunities and open to collaborations. Feel free to reach out via email at any time.
๐ฅ News
- 2026.07: ย ๐๐ One paper Quantization-Robust Unlearning through the Lens of Retain-Forget Loss Landscapes Interaction is accepted at COLM 2026! We extend the idea of NPFT to ML unlearning !
- 2026.05: ย ๐๐ I am honored to be awarded the Silver Reviewer Award by ICML 2026 ๏ผ
- 2026.04: ย ๐๐ One paper GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs is accepted at ICML 2026!
- 2026.02: ย ๐๐ Extend research internship at Panasonic AI, will focus on efficient Agent !
- 2025.11๏ผย ๐๐ Passed my PHD qualify exam. PHD candidate now!
- 2025.09๏ผI am honored to be awarded the ICCV Broad Participation (BP) Award ๏ผ
- 2025.09๏ผI will give a live talk about our ICCV work in the AI TIME ่ฎบ้ WeChat public channel.
- 2025.08: ย ๐๐ One first-authored paper FIER: Fine-Grained and Efficient KV Cache Retrieval for Long-context LLM Inference is accepted at EMNLP 2025 Findings!
- 2025.08: ย ๐๐ I will join Panasonic AI as a remote intern this semester!
- 2025.06: ย ๐๐ One paper MSQ: Memory-Efficient Bit Sparsification Quantization is accepted at ICCV 2025! See you in Hawaii!
- 2025.04: ย ๐๐ I am selected as a DAC Young Fellow at the 62nd Design Automation Conference. See you in SF!
- 2025.02: ย ๐๐ One first-authored paper Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization is accepted at CPAL 2025! See you in Stanford!
๐ Selected Publications (*Equal contribution)
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EMNLP 2025 Findings: FIER: Fine-Grained and Efficient KV Cache Retrieval for Long-context LLM Inference [PDF] [CODE]
Dongwei Wang, Zijie Liu, Song Wang, Yuxin Ren, Jianing Deng, Jingtong Hu, Tianlong Chen, Huanrui Yang. -
CPAL 2025: Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization [PDF] [CODE]
Dongwei Wang, Huanrui Yang. -
Axiv 2026: MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM [PDF]
Dongwei Wang, Jinhee Kim, Seokho Han*, et al. -
COLM 2026: Quantization-Robust Unlearning through the Lens of Retain-Forget Loss Landscapes Interaction
Jialu Wang, Jianing Deng, Shuqing Luo, Yuanzhe LI, Dongwei Wang, Jingtong Hu, Huanrui Yang, Song Wang, Tianlong Chen. -
ICML 2026: GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs [PDF] [CODE]
Jianing Deng, Song Wang, Dongwei Wang, Zijie Liu, Tianlong Chen, Huanrui Yang, Jingtong Hu. -
ICCV 2025: MSQ: Memory-Efficient Bit Sparsification Quantization [PDF] [CODE]
Seokho Han, Seoyeon Yoon, Jinhee Kim, Dongwei Wang, Kang Eun Jeon, Huanrui Yang, Jong Hwan Ko.
For full publications: [Google Scholar]
๐ Honors and Awards
- 2026 ICML Silver Reviewer Award
- 2026 AI Ignite Showcase Runner-Up Award (ECE of UArizona)
- 2025 DAC Young Fellow
- 2025 ICCV Broaden Participitation Award
๐ป Internships
- 2025.08 - 2025.12, Panasonic AI, US.
- 2026.02 - 2026.05, Panasonic AI, US.
๐ Academic Services
I have served as the reviewer for :
- Neurips, CVPR, ICML, TNNLS
๐ Visits