I am a research scientist at Google DeepMind (previously 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, systems for machine learning, and sustainable 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.