What is the Institute for Data Engineering and Science?
The Institute for Data Engineering and Science (IDEaS) provides a unified point to connect government, industry, and academia to advance foundational research, and accelerate the adoption of Big Data technology. IDEaS leverages expertise and resources from throughout Georgia Tech's colleges, research labs, and external partners, to define and pursue grand challenges in data science foundations and in data-driven discovery. We are also dedicated to educating students and those already in the workforce through innovative educational and training programs.
Georgia Tech, along with the University of North Carolina’s Renaissance Computing Institute (RENCI), co-directs the South Big Data Regional Innovation Hub that serves 16 Southern states and the District of Columbia. It is part of the National Science Foundation’s four Regional Innovation Hubs, created to build innovative public-private partnerships addressing regional challenges from data analysis and research to data science workforce development. The Georgia Tech location is operationally run as a center of the Institute for Data Science and Engineering.
The Transdisciplinary Research Institute for Advancing Data Science (TRIAD) integrates research and education in mathematical, statistical, and algorithmic foundations for data science. Funded by the National Science Foundation as part of their TRIPODS program, it is based at Georgia Tech and includes members from the School of Mathematics, the College of Computing, the School of Industrial and Systems Engineering, the School of Electrical and Computer Engineering, and many more.
The Center for High Performance Computing (CHiPC) advances the state of the art in massive data and high-performance computing technology, and solves high-impact real-world problems. HPC scientists devise computing solutions at the absolute limits of scale and speed. In this compelling field, technical knowledge and ingenuity combine to drive systems using the largest number of processors at the fastest speeds with the least amount of storage and energy. The center's focus is primarily on algorithms and applications.
Featured Research Areas
Unstructured and dynamic data analysis, deep learning, data mining, and interactive ML underpin big data foundations and applications.
Health & Life Sciences
Driving predictive, preventive, & personalized care using big data sets from genomics, systems biology, proteomics, and health records.
Materials & Manufacturing
Microscopic views of materials and scalable modeling and simulation technologies for accelerated development of new materials.
Sensors and Internet of Things enable infrastructure monitoring. Data analytics improves energy production, transmission, distribution, and utilization.