IDEaS in Overview
Download a PDF copy of the IDEaS brochure.
The Institute for Data Engineering and Science provides the coordination and expertise necessary to link researchers across the Institute, strengthening Georgia Tech's position in big data. The IRI links research centers and efforts horizontally in foundational areas such as machine learning, high-performance computing, and algorithms. It also drives research within disciplines such as precision medicine, materials science, energy, and smart cities, giving researchers what they need to innovate and pursue challenges on a much larger scale than would otherwise be possible. IDEaS creates meaningful partnerships and accessible resources and educates future data science leaders. It also addresses long-standing challenges in the world of big data, moving research through the innovation stage to accelerating adoption.
As a key tenant of the recently opened Coda building in Midtown’s Technology Square, IDEaS goes hand in hand with the building project. It facilitates new ventures and industrial collaboration between the building’s research neighborhoods, providing a unique opportunity for academia to rub shoulders with industry and be an asset to other premier education, research, and public-serving institutions in Georgia, particularly Emory University and the Centers for Disease Control. IDEaS also collaborates with several stakeholders in the State of Georgia, including the Technology Association of Georgia and the Georgia Manufacturing Extension Partnership, and serves as an incubator for economic development opportunities.
Strategic Goals
IDEaS defines and pursues grand challenges in data science foundations and in data-driven discovery in engineering and sciences in an interdisciplinary multi-investigator endeavor. Affiliated faculty and researchers in IDEaS educate and train students and those already in the workforce through innovative education and programs. It also engages the government, industry, and general public, and accelerates industry adoption and use of big data technologies, with specific goals to:
- Bring together research centers and efforts horizontally in big data foundations (machine learning, high-performance computing, and algorithms) and catalyze data-driven research vertically in important domains (precision medicine, materials science, and energy, etc.)
- Empower and assist other Interdisciplinary Research Institutes in their spheres of operation where big data dominates.
- Direct industry looking for partnership and solutions in data analytics to the best collaborative match.
- Educate and train future data science leaders in academia, government, and industry.
- Serve as a focal point for the creation of a workforce trained in data science, and as a creator and incubator of economic opportunities in the big data era.
