Yueying (Lisa) Li

Yueying (Lisa) Li

Graduate Student in Computer Science

Cornell University


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.

  • Artificial Intelligence
  • Computer System, Computer Architecture
  • Reinforcement Learning
  • Visiting PhD in CSAIL, 2023

    Massachusetts Institute of Technology

  • PhD in Computer Science, 2020

    Cornell University

  • BSc in Computer Engineering, Minor in Math (Highest Honors), 2017

    University of Michigan

  • BSc in Electrical and Computer Engineering, 2015

    Shanghai Jiao Tong University

Recent News

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[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.

Selected Awards

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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

Intern Experience

Microsoft Research
Research Intern
Microsoft Research
Jun 2022 – Present Remote

Responsibilities include:

  • Cloud efficiency group
  • Machine learning modeling and system deployment
Intel Labs
Research Intern
Intel Labs
Jun 2021 – Dec 2021 Remote

Responsibilities include:

  • System and software research group - performance optimization and tracing
  • New architecture feature exploration
ASIC Design Engineer
Aug 2019 – Aug 2020 Cupertino, CA

Responsibilities include:

  • Architecture exploration with new ISA simulator
  • Working on apple matrix engine and memory compression engine

Recent Publications

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(2022). Efficient Planning in a Compact Latent Action Space. OfflineRL@ NeurIPS'2022.

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(2022). Anonymized Title (Under Review). ASPLOS 2023 (In submission).


(2022). Ditto: End-to-End Application Cloning for Networked Cloud Services. ASPLOS 2023.


(2022). STAMP: Lightweight TEE-Assisted MPC for Efficient Privacy-Preserving Machine Learning. Arxiv (In submission).

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