🎓 About Me

📝 My research focuses on Efficient AI, with a focus on efficient deployment and adaptation of LLMs.

🤝 Actively looking for Summer 2026 internship opportunities and open to exciting collaborations. Feel free to reach out via email at any time.

🔥 News

2025.11： 🎉🎉 Passed my PHD qualify exam. PHD candidate now!
2025.09：I am honored to be awarded the ICCV Broad Participation (BP) Award ！
2025.09：I will give a live talk about our ICCV work in the AI TIME 论道 WeChat public channel.
2025.08: 🎉🎉 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: 🎉🎉 I will join Panasonic AI as a remote intern this semester!
2025.06: 🎉🎉 One paper MSQ: Memory-Efficient Bit Sparsification Quantization is accepted at ICCV 2025! See you in Hawaii!
2025.04: 🎉🎉 I am selected as a DAC Young Fellow at the 62nd Design Automation Conference. See you in SF!
2025.02: 🎉🎉 One first-authored paper Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization is accepted at CPAL 2025! See you in Stanford!

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.
ICCV 2025: MSQ: Memory-Efficient Bit Sparsification Quantization [PDF]
Seokho Han, Seoyeon Yoon, Jinhee Kim, Dongwei Wang, Kang Eun Jeon, Huanrui Yang, Jong Hwan Ko.
CPAL 2025: Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization [PDF] [CODE]
Dongwei Wang, Huanrui Yang.

For full publications: [Google Scholar]