Shuangyu Lei

CS Ph.D Student
Jan, 2003
Ithaca, NY, US
sl3535@cornell.edu

About Me

Hello! I am a second-year Ph.D. student in the Department of Computer Science at Cornell University. Currently, I am working with Prof. Hakim Weatherspoon.

My research focuses on computer systems including distributed systems and machine learning systems, particularly on improving their privacy, reliability, and efficiency.

Before joining Cornell University, I received my B.S.E in Computer Science at the University of Michigan with Summa Cum Laude, and B.Eng in Electrical and Computer Engineering at Shanghai Jiao Tong University with Honors. During my undergraduate studies, I collaborated with Prof. Ryan Huang and Prof. Manos Kapritsos on system researches.

Education

Aug 2024 - Present
Ph.D. in Computer Science
Cornell University
Aug 2022 - May 2024
B.S.E in Computer Science
University of Michigan
Aug 2020 - Aug 2024
B.E. in Electrical and Computer Engineering
Shanghai Jiao Tong University

Interests

Distributed Systems
Operating Systems
Scheduling
Containerization

Awards & Scholarships

Cornell Outstanding Teaching Assistant Award
2025
UMich Summa Cum Laude
2024
SJTU Outstanding Graduate
2024
UMich University Honor
2023
UMich Dean's Honor List
2022, 2023
SJTU Undergraduate Excellent Scholarship
2022

Selected Research

Privacy-Preserving Federated Learning Framework via Confidential Containers & KubeStellar
Advisor, 
Prof. Hakim Weatherspoon
Aug. 2024 - Present
Cornell University
#Containerization
#Distributed Systems
#Machine Learning
#KubeStellar

Developing a private computation space evaluating ML model for Digital Agriculture via KubeStellar & Secure Enclaves

Mitigating Application Resource Overload with Targeted Task Cancellation
Yigong Hu, 
Zeyin Zhang, 
Yicheng Liu, 
Yile Gu, 
Shuangyu Lei, 
Baris Kasikci, 
Ryan Huang
Mar. 2023 - Feb. 2024
Symposium on Operating Systems Principles (SOSP) 2025
#Scheduling
#Distributed Systems
#Operating Systems
#Golang

Develop a preemptive scheduling library aiming to enhance system performance utilizing application-implemented cancel mechanisms.

Detecting Privacy and Security Errors in Federated Learning Frameworks
Advisor, 
Prof. Hakim Weatherspoon
Aug. 2025 - Present
#Reliability
#Distributed Systems
#Machine Learning

Detecting Privacy and Security Errors in Federated Learning Frameworks.

Developing Techniques to Test Correctness of Formal Specifications
Advisor, 
Prof. Manos Kapritsos
Oct. 2022 - Mar. 2023
University of Michigan
#Formal Verification
#Dafny
#Distributed Systems

Explore techniques for testing the correctness of formal specifications, a crucial aspect given that the reliability of formal verification projects relies on accurate specifications, an area lacking awareness and techniques.

Last Updated on Oct 24th 2025