Machine Learning (ML) is a field that focuses on the construction and study of algorithms that can analyze data, and learn from, to categorize, and make predictions. It advances and crosses many disciplines that use data to discover scientific principles and infer patterns underlying the dynamics, structures, and functions of artificial and living systems. As such, Machine Learning affects a wide variety of application domains ranging from health care (at varying levels from health records to genomic data) to autonomous systems (including self-driving cars and manufacturing robots) to any form of data analytics, mining, and exploration in biology, economics, finance, and social networks, to deploying and using Internet of Things, to building Artificial Intelligence (AI) and autonomous systems.
Machine Learning at Georgia Institute of Technology (ML@GT) is a new interdisciplinary research center that will serve as a home to education and research around ML and related fields. Our vision statement is "to establish a sustainable research entity that leverages the GT interdisciplinary context, houses current leaders in Machine Learning, and trains the next generation of ML pioneers.” Furthermore, we seek to (a) establish research paradigms that move us from the era of aggregation to the era of sensemaking and discovery, (b) impact all workflows and improve them with data analysis and knowledge extraction, (c) establish a research and academic hub for rigor, depth, and foundation in Machine Learning, and finally (d) establish a premiere home for research that impacts academia, industry, government, and startups