Welcome to IDEaS
The Institute for Data Engineering and Science is one of Georgia Tech’s 10 interdisciplinary research institutes (IRIs), providing the coordination and expertise necessary to link researchers across the Institute by strengthening Georgia Tech's position in big data. IDEaS connects research centers and efforts 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 bigger scale than would otherwise be possible.
Event Spotlight
Generative AI Helps One Express Things for Which They May Not Have Expressions (Yet) -- But Perhaps at The Cost of One's Time and Voice
Featuring Bob Sturm | Associate Professor, Royal Institute of Technology, Stockholm, Sweden
February 5, 2024 | 2:00PM | ONLINE SEMINAR
Zoom Link |https://gatech.zoom.us/j/91988929722 pwd=amZwYWxnRkJuK3JsU3IyVW5udUtwdz09
Abstract: I will discuss some of my creative work engaging with generative AI for music, in both the symbolic and audio sample domains, and focus on three observations in particular. The first observation is that generative AI can provide unanticipated opportunities for creation. The raw materials generated by these methods can provide a bonanza of inspiration, assuaging one's personal inertia, fears, insecurities, and whatnot. I have found this, in the best cases, to jump-start my creative process and facilitate flow. The second observation is that generative AI can confront one with too many attractive options, depending on how good it is of course. I have found that the "lottery"-like function of generative AI can become an attention sink, and I desire methods for efficiently searching the creative space of these models. The third observation is that some materials generated by AI might not be "raw" enough, which is to say they leave no room for one's voice. In some work I have created with generative AI I see and hear very little of me in it. This has led me to think what exactly my voice looks and sounds like, and how I might use generative AI to explicitly serve it. My talk will be illustrated by several audiovisual works.
Learn More Here
Atlanta Workshop for Single-Cell Omics
April 11-12, 2024
Georgia Institute of Technology
Marcus Nanotechnology Building | 345 Ferst Drive NW | Atlanta, GA 30322
Bridging key strengths in single cell genomics at Georgia Tech, Emory University, and Morehouse School of Medicine, all located in Atlanta, Georgia, this workshop showcases our expertise and will feature keynote speakers from across America.
This two-day workshop highlights short talks in the areas of bioinformatics/single-cell analytics and experimental applications of single-cell technologies (e.g., scRNAseq, snATACseq, spatial transcriptomics) for biological, clinical, and translational research.
Centers
The South Big Data Innovation Hub
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.
Transdisciplinary Research Institute for Advancing Data Science
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.
Center for High Performance Computing
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
Machine Learning
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.
High Performance Computing
High-performance systems, middleware, algorithms, applications, software, and frameworks for data-driven computing.
Materials & Manufacturing
Microscopic views of materials and scalable modeling and simulation technologies for accelerated development of new materials.
Energy Infrastructure
Sensors and Internet of Things enable infrastructure monitoring. Data analytics improves energy production, transmission, distribution, and utilization.
Algorithms & Optimization
Streaming and sublinear algorithms, sampling and sketching techniques, high-dimensional analysis for big data analytics.
