Professor Lin Tan

Professor Lin Tan joined Purdue University's Department of Computer Science in 2019 as an associate professor. After establishing a proven track record of research and teaching, she was awarded the named professorship Mary J. Elmore New Frontiers Associate Professor of Data Science.

Her research interests include AI and software synergy, software engineering, software reliability and security, and software text analytics. Some of Tan’s research focuses on leveraging machine learning and natural language processing techniques to improve software dependability and using software approaches to improve the dependability of machine learning systems. Before joining Purdue, she was a Canada Research Chair and an associate professor at the University of Waterloo. Tan earned her PhD in Computer Science in 2019 from the University of Illinois Urbana-Champaign.

Tan was named a Distinguished Member by the Association for Computing Machinery (ACM). She is an IEEE senior member and has co-authored papers that have received ACM SIGSOFT Distinguished Paper Awards at ASE 2020, MSR 2018, and FSE 2016; and IEEE Micro's Top Picks in 2006. Additionally, Tan was a recipient of Canada Research Chair (one of Canada's highest research honors), an NSERC Discovery Accelerator Supplements Award, an Ontario Early Researcher Award, among several other awards.

Tan's service experience also includes co-chair for several conferences – including FSE 2020 Visions and Reflections and MSR 2017 – as well as serving as an editor of IEEE Transactions on Software Engineering and the Springer Empirical Software Engineering Journal.