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). My research interests include compilers, machine learning for systems, program synthesis, and energy-aware computing. I completed a PhD in Computer Science at UC Berkeley. 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. I was a recipient of Microsoft Research PhD Fellowship and Qualcomm Innovation Fellowship.