Beidi Chen is a Postdoctoral scholar in the Department of Computer Science at Stanford University, working with Dr. Christopher Ré. Her research focuses on large-scale machine learning and deep learning. Specifically, she designs and optimizes randomized algorithms (algorithm-hardware co-design) to accelerate large machine learning systems for real-world problems. Prior to joining Stanford, she received her Ph.D. in the Department of Computer Science at Rice University, advised by Dr. Anshumali Shrivastava. She received a BS in EECS from UC Berkeley in 2015. She has held internships in Microsoft Research, NVIDIA Research, and Amazon AI. Her work has won Best Paper awards at LISA and IISA. She was selected as a Rising Star in EECS by MIT and UIUC.
Yanqi Zhou is currently a senior research scientist at Google Brain, Mountain View, working with James Laudon. She pursued her Ph.D. degree at Princeton University. Her research interest lies in computer systems and machine learning. More specifically, Yanqi works on ML and deep RL methods for computer systems and builds large-scale deep learning models for speech and language tasks.