Summary
Lin Tan is a Mary J. Elmore New Frontiers Professor at Purdue University and an Amazon Scholar with 13 years of experience at the intersection of software engineering and AI. Her research focuses on neurosymbolic AI, LLMs for code, auto-formalization, and trustworthy software defect detection and repair, blending NLP, ML, and formal methods to improve software dependability. She has a PhD from UIUC and a B.S. from Zhejiang University, and translates deep research into practical tools for testing and hardening both traditional software and deep learning systems. Known for probing defect characteristics and applying packet-filtering techniques to security, she uniquely bridges low-level systems work with high-level language models. Outside academia she signals a coder’s curiosity—“SwimBytes” hints at a playful, hands-on approach to code and experiments.
13 years of coding experience
Doctor of Philosophy (PhD), Doctor of Philosophy (PhD) at University of Illinois Urbana-Champaign
Bachelor of Science (B.S.), Bachelor of Science (B.S.) at Zhejiang University