I am a research scientist at Google Brain, where I lead Machine Learning for Machine Learning Compilers effort (one of Google Brain moonshots in 2020).
I completed my PhD in Computer Science at UC Berkeley, advised by Ras Bodik and Kathy Yelick. I was a visiting student at the University of Washington for the last two years of my PhD. My dissertation focuses on synthesis-aided compilation and programming models for emerging architectures, ranging from an ultra-low-power processor to a programmable network card. During my undergraduate at MIT, I did research with Saman Amarashinghe on an auto-tuning compiler for heterogeneous systems.