Institute for Data, Econometrics, Algorithms, and Learning (IDEAL), a consortium of more than 50 Chicago-area researchers from Northwestern University, the University of Chicago, the University of Illinois Chicago, and Toyota Technological Institute have been awarded a $20 million grant to accelerate innovations in data science.
IDEAL focuses its research on key aspects of data science foundations across computer science, electrical engineering, mathematics, and statistics in fields such as economics, operations research, and law.
IDEAL researchers promise the work conducted with the TRIPODS funding will lead to new theoretical frameworks, models, mathematical tools, and algorithms for analyzing high-dimensional data, inference, and learning. The goal is to gain a better understanding of the foundations of data science and machine learning in emerging concerns such as reliability, fairness, privacy, and interpretability as data science interacts with society.
IDEAL’s proposal also includes a strong public outreach component to impact research and educational infrastructures to engage a diverse population from underrepresented communities engaged in data science. This includes conducting public lectures and exhibits through a partnership with the Museum of Science and Industry, as well as conducting workshops with local high school teachers through a partnership with Math Circles of Chicago. Direct workshops with undergraduate and high school students are also a part of the strategy.
The NSF announced award winners of its Transdisciplinary Research in Principles of Data Science (TRIPODS) Phase II program, which brings together scientists and engineers from different research communities to further the theoretical foundations of data science through integrated research and training activities. Jinqiao “Jeffrey” Duan, professor of applied mathematics at Illinois Tech, and Binghui Wang, assistant professor of computer science at Illinois Tech, are part of the coalition that received a TRIPODS grant.
TRIPODS is one initiative of NSF’s Harnessing the Data Revolution Big Idea, which is designed to stimulate discovery and innovation in data science algorithms, data infrastructure, and education and workforce development.
