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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: June 27, 2019
The Board of Regents of the University System of Georgia has appointed Professor Haesun Park to be a Regents Professor. Dr. Park is the Director of the Center for Data Analytics and a Professor of Computational Science and Engineering in the College of Computing at Georgia Tech. She is a frequent collaborator with Brook Byers Institute for Sustainable Systems’ projects and proposals.
Regents' Professorships are awarded to distinguished faculty whose scholarship or creative activity is recognized both nationally and internationally as innovative and pace-setting. A Regents’ Professorship is awarded by the Board of Regents with the unanimous recommendation of the USG institution President, chief academic officer, appropriate academic dean, and three other members of the faculty named by the President, and upon the approval of the Board of Regents Chancellor and the Committee on Academic Affairs. Appointments are for three years, with a renewal for a second three year term. Thereafter the appointment is to be renewed at the discretion of the President of institution to which the faculty member has affiliation.
Professor Park was elected as a SIAM Fellow in 2013 and IEEE Fellow in 2016 for her outstanding contributions in numerical computing, data analysis, and visual analytics. She was the Executive Director of Center for Data Analytics 2013-2015 and was the director of the NSF/DHS FODAVA-Lead (Foundations of Data and Visual Analytics) Center 2008-2014. She has published extensively in the areas of numerical computing, large-scale data analysis, visual analytics, text mining, and parallel computing.