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Kexin Pei is an Assistant Professor in the Department of Computer Science at the University of Chicago. His research operates at the intersection of Security, Software Engineering, and Machine Learning, with a focus on developing data-driven program analysis approaches that enhance the security and reliability of traditional AI-based software systems. He is particularly excited about designing machine learning models that can effectively reason about program structure and behavior, facilitating the efficient analysis, detection, and remediation of software bugs and vulnerabilities. Kexin's work has been recognized with a Paper Award from the ACM Symposium on Operating Systems Principles (SOSP) and a Distinguished Artifact Award, and he has been featured in a Communications of the ACM Research Highlight. Additionally, he was a top-10 finalist in the CSAW Applied Research Competition. Currently, he collaborates with the Learning Code team at Google DeepMind, where he builds program analysis tools based on large language models.
Department of Philosophy