Analyzing and Securing Software with Robust and Generalizable Learning
|Event Date:||January 25, 2023|
|Contact Name:||MSEE 239
|School or Program:||Electrical and Computer Engineering
Kexin Pei is a Ph.D. candidate in Computer Science at Columbia University, advised by Suman Jana and Junfeng Yang. His research lies at the intersection of security, software engineering, and machine learning, with a focus on building machine-learning tools that utilize program structure and behavior to analyze and secure software. His research has received the Best Paper Award in SOSP, a Distinguished Artifact Award, been featured in CACM Research Highlight, and won CSAW Applied Research Competition Runner-Up. He was part of the learning for code team when he interned at Google Brain, building program analysis tools based on large language models.
Ryan Newton, email@example.com
2023-01-25 08:00:00 2023-01-25 17:00:00 America/Indiana/Indianapolis Analyzing and Securing Software with Robust and Generalizable Learning Kexin Pei PhD Candidate Columbia University 10:30 am