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.
Visiting PhD in CSAIL, 2023
Massachusetts Institute of Technology
PhD in Computer Science, 2020
BSc in Computer Engineering, Minor in Math (Highest Honors), 2017
University of Michigan
BSc in Electrical and Computer Engineering, 2015
Shanghai Jiao Tong University
[28/11/22] Awarded WiML travel grant for NeurIPS 2022. First-time attendee to share work on ML for Cloud Monitoring. Thank you very much for the inspirational experience!
[01/10/22] Co-organized the JOBS workshop at MICRO-55. Check out the career advices from academia and industry.
[22/10/22] Submitted one paper to ASPLOS on scheduling in collaboration with Cornell, MIT, Stanford, and Intel Labs. Thank you for the generous support! Fingers crossed.
[28/08/22] Presented my internship findings in MSR. Thank you very much for the nice intern experience!
[28/06/22] Co-organized CASA Summer DEI reading group, and initiated datacenter reading group. Please feel free to message me for more information.
Departmental Fellowship (Cornell University), 2020
Outstanding Graduate of Shanghai, 2019
GSFEI Top Scholar Recruitment Award (University of Washington), 2019
University Honors, Dean’s List (All semesters) (University of Michigan)
Meritorious Winner, Mathematical Contest in Modeling, 2018
National Scholarship (2%), 2017