National Science Foundation Awards $20 Million To Universities For Advanced Data Science

The National Science Foundation (NSF) has announced awards totaling $20 million that will fund two multi-university teams of scientists and engineers who will conduct advanced research and training in the field of data science.

The awards come in the form of Transdisciplinary Research in Principles of Data Science, or TRIPODS, Phase II grants, a part of NSF’s Harnessing the Data Revolution Big Idea, which aims to accelerate discovery and innovation in data science algorithms, infrastructure, and education and workforce development.

“The NSF TRIPODS Institutes will bring advances in data science theory that improve health care, manufacturing, and many other applications and industries that use data for decision-making,” said NSF Division Director for Electrical, Communications and Cyber Systems Shekhar Bhansali in the agency’s announcement.

TRIPODS awards aim to bring together experts in the disciplines of electrical engineering, mathematics, statistics, theoretical computer science and other fields to develop a unified foundation for data science.

The NSF grants will support two new teams over five years to work on these topics.

The first is the Institute for Emerging CORE Methods in Data Science, or EnCORE, led by the University of California San Diego in collaboration with the University of California, Los Angeles; University of Pennsylvania; and The University of Texas at Austin.

Working with scientists from disciplines such as statistics, mathematics, electrical engineering, theoretical computer science, machine learning and health science, the EnCORE team will focus on the four CORE pillars of data science: C for complexities of data, O for optimization, R for responsible learning, and E for education and engagement.

The institute will also foster broadened participation in data science by engaging students of diverse backgrounds at all levels, from K-12 to postdocs and junior faculty. According to NSF, the project aims to reach a wide demography of students by offering collaborative courses across its partner universities and a flexible co-mentorship plan for multidisciplinary research.

The component awards for this institute can be found here: UC San Diego, UCLA, University of Pennsylvania, and The University of Texas at Austin.

The second grant will establish the Institute for Data, Econometrics, Algorithms, and Learning, or IDEAL, a multi-disciplinary effort led by the University of Illinois Chicago in collaboration with Northwestern University; Toyota Technological Institute at Chicago; the University of Chicago; and Illinois Institute of Technology, in partnership with members of the Learning Theory team at Google.

Involving more than 50 researchers across computer science, electrical engineering, mathematics, statistics, economics, operations research and law, this institute will focus on the foundations of machine learning, high-dimensional data analysis and inference, and data science and society.

It also aims to broaden research and education participation by underrepresented groups and will include high school and undergraduate students, as well as teachers (partnering with Math Circles of Chicago) and the public (through lectures in partnership with the Museum of Science and Industry).

The component awards in this grant can be viewed here: UIC, Toyota Technological Institute, The University of Chicago, IIT, Northwestern University.

The two institutes just announced bring the total number of TRIPODS Phase II Institutes to four. Previous TRIPODS Institutes, also involving collaborations between several universities, were announced in 2020.

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