To achieve advances in critical areas of science and technology, Georgia Tech is leveraging its research expertise to transform the ability of individuals and organizations to analyze large and complex sets of data, Big Data. Such an ability can help provide solutions to a wide range of challenges.
For example, the use of Big Data techniques to better understand social networks could help tackle matters such as understanding critical trends in behaviors and customs, and influencing change. These computational capabilities could also be applied to even more taxing issues such as finding vulnerabilities in the power grid and monitoring important protein interactions in cancer research.
Through a number of campus units, including the Institute for Data and High Performance Computing (IDH) and the Georgia Tech Research Institute (GTRI), Georgia Tech supports multidisciplinary research teams that are both developing innovations in computational methods to advance Big Data analysis, and applying these techniques to industry, business, and the public sector. Enabling technologies under development include data visualization, advanced analytics, machine learning, and high-performance computing. Application areas for Georgia Tech’s Big Data research include astrophysics, biomedicine, combustion, energy, finance, health care, manufacturing, materials, information and cybersecurity, social networks, sustainability, and transportation. Both undergraduate and graduate students contribute to research in these critical areas.
Mark Richards, David Bader, and Dan Campbell
(left-to-right) in the Advanced Computing
Technology Lab operated by the Georgia Tech Research
Institute. (Credit: Gary Meek) Full Story >
Another illustration of how Georgia Tech is taking the lead in Big Data is its role as the chief institution for the Foundations on Data Analysis and Visual Analytics (FODAVA) research initiative. For this initiative, it performs foundational research in massive data analysis and visual analytics. Researchers investigate ways to improve the visual analytics of massive data sets through advances in areas such as machine learning, numeric and geometric computing, optimization, computational statistics, and information visualization.
Machine learning, a critical element of the Big Data environment, is a primary focus at Georgia Tech, where researchers are spearheading efforts to build and disseminate scalable machine learning software. Machine learning methods find patterns in data that people may have difficulty identifying, and these methods have applications in virtually every discipline and human enterprise.
Additionally, Georgia Tech provides technical leadership for the national Center for Adaptive Supercomputing Software for Multithreaded Architectures (CASS-MT) and directs efforts within the center to develop methods for analyzing massive and complex semantic networks.