Yueying Li is a PhD student studying the intersection of computer system and machine learning, advised by Prof. Christina Delimitrou and Edward Suh on problems spanning efficient and reliable cloud system. More broadly, I’m interested in system for machine learning and machine learning for system. Specifically, I focus on scheduling policies and mechanisms across different stacks. Last summer I interned at Microsoft Research on automated anomaly detection and root cause analysis for cloud services, and a summer before that, I did research on designing new scheduling abstractions for microservice applications with Intel Labs. I am also a keen observer on recent ML and RL papers, and I also have the fortune to work with Yuandong Tian on efficient planning offline RL; Robbert Van Renesse and Lorenzo on distributed shared log.