معرفی
Kexin Pei is a Neubauer Family Assistant Professor at the Department of Computer Science, University of Chicago. She received her PhD from the Department of Computer Science at Columbia University. Her academic career spans research and teaching in the fields of Security, Software Engineering, and Machine Learning.
Her educational background includes:
- PhD in Computer Science from Columbia University
Dr. Pei's research interests focus on developing data-driven program analysis to improve the security and reliability of both traditional and AI-based software systems. She is particularly interested in creating machine learning models that can reason about program structure and behavior to precisely and efficiently analyze, detect, and fix software bugs and vulnerabilities. Her work bridges the gap between theoretical computer science and practical security applications, with significant contributions to binary analysis, program understanding, and AI security.
Her research output shows a strong trend toward integrating machine learning with traditional program analysis techniques. Many of her recent publications explore how neural networks and language models can enhance software security and reliability, particularly in binary analysis, vulnerability detection, and code understanding. Her work often involves developing novel frameworks that combine execution traces, code structure, and semantic understanding to create more robust analysis tools.
Dr. Pei has received several prestigious awards for her research:
- Best Paper Award at MASEC@NeurIPS 2023
- Best Paper Award Runner-Up in CSAW 2018
- Top-10 Finalist of Applied Research Competition
- ACM SigMobile Research Highlight
- MLSec @NIPS'17
- CACM research highlight
- Distinguished Artifact Award at FSE 2016
Dr. Pei actively mentors students and has advised several PhD and Master's students. Her group includes PhD students Jie Zhu, Weichen Li, and Jun Yang (with Shan Lu), as well as MS students Sam Huang and Yiming Cheng (with Junchen Jiang). She has also worked with numerous student collaborators and visiting students from institutions including MIT, Georgia Tech, and UChicago. Her research has been supported by grants from various sources, including collaborations with Google DeepMind and Microsoft Research where she completed internships.
Dr. Pei is involved in several research labs and teams, including collaborations with the CUMLSec group (as seen in repositories like trex and XDA on GitHub). Her work often involves interdisciplinary teams combining expertise in security, machine learning, and software engineering to tackle complex problems in program analysis.
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