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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Atlanta, GA | Posted: February 3, 2012
Ming Yuan, associate professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), has been awarded the Coca-Cola Junior Professorship for a three-year term.
“During Dr. Yuan’s time on the ISyE faculty, he has made valuable contributions in research, teaching, and service. Dr. Yuan’s exceptional teaching ability is evident in the excellent teaching evaluations and student praise he receives. We are fortunate to have him as a colleague and now as the ISyE’s newest Coca-Cola Junior Professor,” said Jane C. Ammons, H. Milton and Carolyn J. Stewart School Chair.
The Coca-Cola Junior Professorship is supported by a gift from Coca-Cola, in order to support research and development in ISyE. Endowed professorships, such as this one, are awarded to outstanding faculty, ensuring them the resources they need to remain at the forefront of their fields and to lead teaching and research efforts in their key areas.
In addition to this recent honor, Yuan was the recipient of the National Science Foundation Career Award in 2009 for his exemplary work in sparse modeling and estimation with high-dimensional data. He was also named as a Distinguished Cancer Scholar from the Georgia Cancer Coalition in 2007, and was the recipient of the John van Ryzin Award in 2004.
Yuan received his PhD in statistics from the University of Wisconsin at Madison. He also holds a master’s in computer science from the University of Wisconsin, and a bachelor’s in electrical engineering and information science from the University of Science & Technology of China. Yuan's current research interests include statistical learning, bioinformatics, and methods of regularization.