I am Kan Zhu, a second year PhD student at University of Washington’s Paul G. Allen School of Computer Science and Engineering, co-advised by Baris Kasikci and Arvind Krishnamurthy.
I develop systems and methodologies for optimizing Large Language Model (LLM) inference. The widespread adoption of LLMs presents unique challenges for on-device inference and cost-effective large-scale serving due to their substantial computational demands. To address these issues, I am interested in designing innovative hardware, algorithms, and frameworks tailored for both edge devices and data center environments.
Ph.D. in Computer Science and Engineering, 2023 - Present
University of Washington
B.S. Computer Engineering, 2021 - 2023
University of Michigan
B.S. Electrical and Computer Engineering, 2019 - 2021 (transfer to UM)
Shanghai Jiao Tong University