معرفی
Mei Nagappan is an Assistant Professor at the David R. Cheriton School of Computer Science, University of Waterloo. Previously, he held positions as an Assistant Professor at Rochester Institute of Technology and as a Post-Doctoral Fellow at Queen’s University’s Software Analysis and Intelligence Lab (SAIL). His research focuses on leveraging big data for empirical software engineering, particularly mining ultra-large software repositories to identify patterns and relationships in ecosystems. He emphasizes solutions addressing stakeholders beyond developers, such as operators, build engineers, and project managers.
Education: PhD in Computer Science from North Carolina State University under Dr. Mladen Vouk, and postdoctoral work under Dr. Ahmed Hassan. His research spans vulnerability detection, DevOps, AI in programming (e.g., GitHub Copilot analysis), and diversity in software engineering conferences. Key interests include static analysis, security, and the impact of non-traditional backgrounds in SE. He advocates for inclusive practices and evaluates tools like Copilot through a security and user-centric lens.
Research Interests: Big Data Empirical SE, Human-LLM Collaboration, Vulnerability Detection, DevOps, Security, Diversity in SE, Static Analysis Tools. His work bridges theory and practice, with studies on logging practices, build technologies, and mobile app analytics. Recent projects explore barriers faced by non-traditional SE professionals and the effectiveness of AI-driven testing tools.
Grants & Advising: While specific grants are not listed, his research is supported by large-scale empirical studies. Advising focuses on graduate students exploring topics like bug localization, LLM limitations, and diversity metrics in open-source projects. His lab collaborates on tools like AddressWatcher for memory leak analysis and RepoQuester for GitHub project evaluation.
Labs & Teams: Previously associated with SAIL at Queen’s University. Current collaborations involve the Cheriton School’s SE research groups, focusing on AI in software development and empirical studies of developer workflows.
