Lin Tan

Lin Tan is the Mary J. Elmore New Frontiers Associate Professor at Purdue University's School of Electrical and Computer Engineering. Previously, she served as a Canada Research Chair and Associate Professor at the University of Waterloo. Her research focuses on AI-software synergy, software engineering, reliability, and security, leveraging machine learning and NLP to enhance software dependability and improve machine learning systems' robustness.

Lin holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign (2009). She has received prestigious awards including the Canada Research Chair, NSERC Discovery Accelerator Supplements Award, and Ontario Early Researcher Award. Her work has been recognized with ACM SIGSOFT Distinguished Paper Awards and IEEE Micro's Top Picks (2006).

Her service contributions include co-chairing FSE 2020 (Visions and Reflections) and MSR 2017, as well as editorial roles at IEEE Transactions on Software Engineering and Springer's Empirical Software Engineering Journal. Lin’s research bridges software engineering principles with AI, aiming to create resilient systems through interdisciplinary approaches.