Lin Tan

Lin Tan is a Professor of Computer Science at Purdue University, holding the Mary J. Elmore New Frontiers Professorship. She joined Purdue in 2019 after serving as a Canada Research Chair and associate professor at the University of Waterloo. She is an ACM Distinguished Member and IEEE Senior Member.

Education:

• PhD in Computer Science, University of Illinois Urbana-Champaign
• BS in Computer Science and Technology, Zhejiang University

Research Interests:

Professor Tan’s research lies at the intersection of software engineering, artificial intelligence, and security. Her work focuses on software-AI synergy, software dependability, defect detection & repair, and software text analytics. She leverages machine learning and natural language processing to enhance software reliability, and conversely uses software techniques to improve the dependability of AI systems.

Her recent projects include building binary foundation models (Nova), evaluating large language models for code generation and repair, and developing interactive debugging tools that reduce debugging time by one-third. She also explores robot task planning with LLMs and automated front-end development.

Awards & Honors:

• Best Paper Award Finalist, ICRA 2025
• ELATES Fellow, 2024-2025
• ACM SIGSAC Distinguished Paper Award, CCS 2024
• J.P.Morgan AI Faculty Research Awards (2020, 2021, 2022)
• ACM SIGSOFT Distinguished Paper Awards (ASE 2020, MSR 2018, FSE 2016)
• Canada Research Chair (2017)
• Ontario Early Researcher Award (2015)
• NSERC Discovery Accelerator Supplements Award (2015)
• Google Faculty Research Awards (2010, 2014)
• IEEE Micro Top Picks (2006)

Advising & Funding:

Professor Tan currently advises eight PhD students and has graduated 20+ PhD and Master’s students now thriving in academia (York University, Concordia University, University of Alberta) and industry (Microsoft, Meta, Amazon, Google). Her group is generously supported by NSF, Meta/Facebook Research Awards, J.P.Morgan AI Faculty Awards, and NSF REU programs.

Labs & Teams:

She leads the Software Reliability & AI Lab at Purdue, recruiting postdocs, PhD, MS, and undergraduate researchers year-round. Lab interests span binary recovery, LLM-based program repair, testing deep-learning libraries, and data-free model extraction.