About me

I am pursuing a B.Eng. in Automation at Zhejiang University (ranked 47th globally by QS), where I placed first among 113 peers in the “Mixed Class” honors program, with a GPA of 91.81% (3.98/4.0).

I’m fortunate to work with Prof. Yuanchao Shu on bridging the gap between ever-growing AI models and resource-constrained mobile devices. I secured a ¥100,000 undergraduate research grant from the National Natural Science Foundation of China (awarded to only 120 students/year across all fields). Our collaborative LLM fine-tuning framework, Confidant, will be presented at Mobicom'25.

I am currently undertaking a six-month research internship at the University of Chicago with Prof. Junchen Jiang, focusing on KV Cache optimization in LLM inference. I designed a scalable KV Cache quantization and serialization method and actively contribute to the open-source LMCache project.

Currently, my research interests lie in building and optimizing next-generation machine learning systems, particularly in mobile or networked scenarios. I’m also passionate about other computing and networking challenges, such as IoT, ubiquitous computing and wireless communication.

Feel free to contact me at qinyuyang2003@zju.edu.cn or qinyuyang2003@uchicago.edu.