Yuanwei (Kevin) Fang
Yuanwei Fang is a 6th-year Ph.D. candidate in the computer science department of the University of Chicago. He has broad research experience in the entire stack of a computing system, with a focus on computer architecture, compiler, database, operating system and distributed system.
Throughout his Ph.D. career, Yuanwei spent most of his time on accelerating data analysis in the emerging data lake paradigm. To facilitate fast analysis on raw, messy and heterogeneous data, he designed and implemented a data transformation hardware accelerator and the associated instruction set. He also developed a customized compiler toolchain for easy programming the accelerator. He used that toolchain to write a set of representative accelerated computation kernels. He developed a light-weight runtime system for the accelerator management, and later, an extended data analytic system from Apache Spark with the embedded superior data transformation capability from the accelerator/runtime he designed. The entire software/hardware system is prototyped on an Intel CPU-FPGA platform.
Yuanwei is the recipient of the Qualcomm Roberto Padovani Award in recognition of his innovative contribution for the company during his internship. He also received the CERES Research Award from the CS department of the University of Chicago. He is under the supervision of Prof. Andrew A. Chien. He received his B.S. in Microelectronics from the Fudan University.
- 9/2018 I completed my internship at Google. I was ranked as "superb" (top 1% Google intern) in my intern evaluation!
- 6/2018 I work with the tech leads from the Google Datacenter platform team, Youtube data warehouse team (Procella), and Sawmill log team for software/hardware co-designing the next generation data analytic system (host: Jichuan, co-host: Biswa ) as a research intern.
- 9/2017 I got MICRO50 student travel award ($500).
- 7/2017 UDP paper got accepted by MICRO50!
- 10/2016 I got the Qualcomm Roberto Padovani Award ($5000) in recogition of innovative contribution to their machine-learning based network application firewall during my internship!