Massive Data Analysis and Visual Analytics

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TITLE: Massive Data Analysis and Visual Analytics: FODAVA activities and Georgia Tech Center Plans SPEAKER: Professor Haesun Park ABSTRACT: In this talk, I will present our research, education, and community building activities as the NSF/DHS FODAVA-Lead (Foundations of Data and Visual Analytics) awardees since the summer of 2008 and the plans to establish the Georgia Tech Massive Data Analysis and Visual Analytics Center. Then I will briefly cover some of my research on dimension reduction of high dimensional data such as generalization of Linear Discriminant Analysis (LDA) for high dimensional under-sampled data sets and the Nonnegative Matrix Factorization (NMF). Some experimental results from text classification, facial recognition, fingerprint classification, and 2D visualization of clustered high dimensional data demonstrate the effectiveness of the LDA based approaches. I will also present one of the fastest algorithms for the NMF and various formulations of the NMF and their applications in data analysis. Bio: Prof. Haesun Park received her B.S. degree in Mathematics from Seoul National University, Seoul Korea, in 1981 with summa cum laude and the University President's Medal for the top graduate, and her M.S. and Ph.D. degrees in Computer Science from Cornell University, Ithaca, NY, in 1985 and 1987, respectively. She was on the faculty of the Department of Computer Science and Engineering, University of Minnesota, Twin Cities, from 1987 to 2005. From 2003 to 2005, she served as a program director for the Computing and Communication Foundations Division at the National Science Foundation, Arlington, VA, U.S.A. Since July 2005, she has been a professor in the Computational Science and Engineering Division at the Georgia Institute of Technology, Atlanta, Georgia where she is currently the associate chair. Her research interests include numerical algorithms, data analysis, bioinformatics, and parallel computing. She has published over 120 refereed research papers in these areas. She is the director of the NSF/DHS FODAVA (Foundations of Data and Visual Analytics) project where the goal is to create mathematical and computational foundations for data and visual analytics which is a newly emerging discipline of science of analytical reasoning facilitated by data analysis and interactive visualization. Prof. Park has served on numerous conference committees including conference co-chair for SIAM International Conference for Data Mining in 2008 and 2009. Currently she is on the editorial board of BIT Numerical Mathematics, SIAM Journal on Matrix Analysis and Applications, Statistical Analysis and Data Mining, and International Journal of Bioinformatics Research and Applications.


  • Workflow Status: Published
  • Created By: Anita Race
  • Created: 10/12/2009
  • Modified By: Fletcher Moore
  • Modified: 10/07/2016


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