Chung-Yi Weng - University of Washington
I am a privacy engineer at Snap Inc. My research interest is in federated learning and differential privacy. I am also interested in lower bounds and hardness results in computational complexity. Previously, I worked at ByteDance, focusing on privacy-preserving machine learning and large language models. Before that, I received Ph.D. in the Paul G. Allen School of Computer Science & Engineering at the University of Washington in 2020. I was fortunate to be advised by Professor Paul Beame and Professor Kevin
( * alphabetic author order)
Number Balancing is as hard as Minkowski′s Theorem and Shortest Vector , Rebecca Hoberg * , Harishchandra Ramadas * , Thomas Rothvoss * , Xin Yang * , IPCO 2017 , Arxiv .
Chung-Yi Weng - University of Washington