About the Center for Applied Algorithms
In the age of information, there is a wealth of data from observational, industrial, or experimental sources such as social media, financial markets, or scientific data. As the ability of systems and infrastructures to produce data outpaces our ability to process the information, we increasingly rely on new "big data" techniques to efficiently extract crucial information so that we are better informed to make insightful decisions in complex conditions.
At the Center for Applied Algorithms, our mission is to provide next-generation foundations that attack the heart of big data through innovative but analytically-grounded techniques that are scalable, accurate, and efficient. Our goal is to bring together algorithmic, mathematical, and statistical components of data science through a common language that unites researchers from science, technology, engineering, and mathematics (STEM) and ultimately build a foundation that stimulates multidisciplinary collaboration.
At the heart of our approach is the design of scalable algorithmic methods that provide tradeoffs between the competing notions of desirable accuracy and desirable performance speedups, ultimately providing principled sublinear approaches to decision making in complex environments. Our vision is to deploy practical systems that can enable diverse science and engineering applications to achieve orders-of-magnitude improvement in scalability, cost, and responsiveness.