Research Overview


IDEAS: The new home of big data research and solutions

Recognizing the importance of big data and high performance computing, Georgia Tech is embarking on the construction of a 21+ story building and an 80,000 sq. ft. data center to support data science and high performance computing. IDEAS will be an anchor tenant of the new “Coda” building, to be built in Midtown Atlanta by Jan 2019. It will lead in the transition of the computing industry from its compute-centric roots to its data-centric future. This will entail facilitating the restructuring of the modern computing ecosystem to be centered on the secure and timely acquisition, distillation, storage, modeling, and analysis of data in driving decisions in all sectors of the economy.

Big Data


Data Science is an interdisciplinary field that is concerned with systems, storage, software, algorithms, and applications for extracting knowledge or insights from data. Data driven research is also commonplace in many fields of sciences and engineering, where direct observations (astronomy), instrumentation (sensors, DNA sequencers, electron microscopes), or simulations, (molecular dynamics trajectories), generate datasets that must be analyzed with domain-specific knowledge. Recently, our ability to collect and store massive datasets that are typically characterized by high volume, velocity, or variety, and inadequacy of current techniques to handle such large data sizes, led to the coining of the term “Big Data.”


IDEAS Research Areas


Machine Learning
Underpins the transformation of data to knowledge to actionable insights. Research in unstructured and dynamic data, deep learning, data mining, and interactive machine learning advances foundations and big data applications in many domains.

High Performance Computing
Critical technology for big data analysis. High performance systems, middleware, algorithms, applications, software, and frameworks support data-driven computing at all levels.

Algorithms and Optimization
Algorithms, optimization, and statistics are laying the foundations for large-scale data analysis. Streaming and sublinear algorithms, sampling and sketching techniques, high-dimensional analysis are enabling big data analytics.

Health and Life Sciences
Big data sets abound in genomics, systems biology, and proteomics. Advances in electronic medical records, computational phenotyping, personalized genomics and precision medicine are driving predictive, preventive, and personalized healthcare.

Materials and Manufacturing
Large-scale data sets providing microscopic view of materials, and scalable modeling and simulation technologies, are paving the way for accelerated development of new materials.

Energy Infrastructure
Advances in sensors and Internet of Things enable energy infrastructure monitoring. Data analytics brings unparalleled efficiencies to energy production, transmission, distribution, and utilization.

Smart Cities
Achieving efficient use of resources and services, safety, affordability, and a higher quality of life using data-based research. Internet of Things research uses big data and analytics from massive streams of real-time data and applies it to smart city initiatives.