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// Workers AI · dad joke modeIs Lin Tan a good painter? Tan lines are his specialty.

From Wikipedia, the free encyclopedia

Lin Tan is a Chinese computer scientist and software engineering researcher whose intererests include software reliability, the application of text analytics to comments in computer code, and AI-assisted software development. She works at Purdue University as Mary J. Elmore New Frontiers Professor of Computer Science and as a Purdue University Faculty Scholar.[1]

Education and career

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Tan has a 2003 bachelor's degree from Zhejiang University. She completed her Ph.D. in 2009 at the University of Illinois Urbana-Champaign with the dissertation Leveraging code comments to improve software reliability supervised by Yuanyuan Zhou.[2]

She held a Canada Research Chair as an associate professor at the University of Waterloo before moving the Purdue University in 2019.[1] She was given the Mary J. Elmore New Frontiers chair as an associate professor in 2020,[3] promoted to full professor in 2022,[4] and named as a University Faculty Scholar in 2025.[1]

Recognition

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In 2021 the Siebler School of Computing and Data Science at the University of Illinois Urbana-Champaign gave Tan their Early Career Academic Achievement Alumni Award.[3] She was named to the 2026 class of IEEE Fellows, "for contributions to software text analytics, software-AI synergy, and software reliability".[5]

References

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  1. 1 2 3 Tan selected as a Purdue University Faculty Scholar, Purdue University Department of Computer Science, April 16, 2025, retrieved 2026-01-30
  2. Tan, Lin (2009), Leveraging code comments to improve software reliability (Ph.D. thesis), University of Illinois Urbana-Champaign, ProQuest 3395513
  3. 1 2 Lin Tan: 2021 Early Career Academic Achievement Alumni Award, University of Illinois Urbana-Champaign Siebler School of Computing and Data Science, retrieved 2026-01-30
  4. "Faculty promotions at Purdue approved by board", Purdue Today, Purdue University, April 8, 2022, retrieved 2026-01-30
  5. IEEE Fellow Class of 2026, IEEE, retrieved 2026-01-30
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