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Lin Tan is a Professor in the Department of Computer Science at Purdue University. His research interests encompass software dependability, the synergy between software and artificial intelligence, and software text analytics. Tan's work focuses on leveraging machine learning and natural language processing techniques to improve software dependability, as well as employing software approaches to enhance the reliability of machine learning systems. Before joining Purdue University, he was an associate professor and Canada Research Chair at the University of Waterloo. Lin Tan completed his Ph.D. at the University of Illinois at Urbana-Champaign in Computer Science, where he developed a strong foundation in the intersection of software engineering and machine learning.
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