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Please visit IDEAL

In 2022, we won phase II NSF funding and became a part of the Chicago-wide IDEAL institute. This site is therefore no longer being maintained.


This collaborative research institute combines aspects of mathematics, statistics, computer science, and engineering to study the foundations of data science. The institute is a collaboration between three departments: Computer Science (CS), Mathematics, Statistics, and Computer Science (MSCS), and Electrical and Computer Engineering (ECE).

The institute leverages the wide range of expertise among the investigators on this project in the three departments to bring the theoretical foundations of data science closer to the practice of data science. This involves studying idealized models of data, understanding inherent computational limits associated to these idealized models, and then developing models and methods that are robust to realistic models of uncertainty. The institute also focuses on activities surrounding the training of the next generation of researchers.

Research undertaken at the institute research aims to push the boundaries of the theory of data science by both gaining deeper understanding of idealized models and by building a theory around realistic models of data and computation. The themes pursued by this institute will include 1) the representation and structure of data; 2) machine learning and complexity; and 3) robustness and privacy. These themes will serve to link the theory and application of data science and to provide opportunities for the investigators to pool their expertise across the three disciplines of theoretical computer science, mathematical sciences, and electrical engineering.

This institute is funded as part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.