UT ECE Prof. Miryung Kim Receives 2011 Microsoft Software Engineering Innovation Foundation Award

Wednesday, May 4, 2011 - 12:00pm

UT ECE Prof. Miryung Kim Receives 2011 Microsoft Software Engineering Innovation Foundation Award

Miryung Kim Wins SEIF Award

UT ECE professor Miryung Kim has been named a recipient of a 2011 Microsoft Software Engineering Innovation Foundation Award. Microsoft Research presents the Software Engineering Innovation Foundation (SEIF) Awards to support academic research in software engineering technologies, tools, practices, and teaching methods. Projects can be related to any of the core areas of interest in software engineering research and education.

This year, Microsoft Research received about 90 proposals for research grants in seminal software engineering areas, innovative software engineering education methods, and improvements in the
software development process. After a thorough internal review process, they selected 10 proposals this year, including Prof. Kim's proposal titled "RefFinder: An Extensible Framework for Refactoring Reconstruction."

Dr. Miryung Kim is an assistant professor in the Department of Electrical and Computer Engineering at the University of Texas at Austin. She received her B.S. in Computer Science from Korea Advanced Institute of Science and Technology in 2001 and her M.S. and Ph.D. in Computer Science and Engineering from the University of Washington under the supervision of David Notkin in 2003 and 2008 respectively. In addition to the Microsoft SEIF award, Prof. Kim received the IBM Jazz Innovation Award in 2009.

Professor Kim's research focuses on software engineering, specifically on software evolution. Her research group, Software Evolution and Analysis Laboratory (SEAL), develops innovative program analysis algorithms and software development tools to make it easier to develop and maintain large scale software systems. SEAL's mission is to significantly improve programmer productivity and program correctness. She studies software development practices through user studies with professional software and through rigorous empirical analysis of open source project data.

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