The National Science Foundation is investing $20 million to fund two multi-university institutes that will study advanced data science.
The National Science Foundation (NSF) has announced $20 million in awards 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 are Transdisciplinary Research in Principles of Data Science, or TRIPODS, Phase II grants, 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 lead to advances in data science theory that improve health care, manufacturing, and many other applications and industries that use data to make decisions,” said Shekhar Bhansali, director of the NSF Division of Electrical, Communications, and Cyber Systems at the agency. advertisement
The TRIPODS awards aim to bring together experts from electrical engineering, mathematics, statistics, theoretical computing and other fields to develop a common foundation for data science.
The NSF grants will support two new groups over five years to work on these issues.
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 data complexities, O for optimization, R for. responsible study, and E for education and engagement.
The Institute will promote broad participation in data science by involving students from diverse backgrounds at all levels, from K-12 to postdocs and junior faculty. According to NSF, the project aims to reach a broad demographic of students by offering collaborative courses between its member universities and a flexible co-mentorship plan for multidisciplinary research.
Awards from this institute’s constituents can be found at: UC San Diego, UCLA, University of Pennsylvania, and University of Texas at Austin.
The second grant will establish the Institute for Data, Econometrics, Algorithms, and Learning, or IDEAL, a multidisciplinary effort led by the University of Illinois at Chicago in collaboration with Northwestern University; Toyota Institute of Technology in Chicago; University of Chicago; and the Illinois Institute of Technology, in collaboration with members of Google’s Learning Theory team.
Featuring more than 50 researchers from computer science, electrical engineering, mathematics, statistics, economics, operations research and law, this institute will focus on fundamentals of machine learning, high-dimensional data analysis and inference, and data science and society.
It also aims to expand participation in research and education by underrepresented groups, including high school and undergraduate students, as well as teachers (in partnership with Math Circles of Chicago) and the public (through lectures in partnership with the Museum of Science and Industry).
The component awards for this scholarship can be viewed here: UIC, Toyota Technological Institute, The University of Chicago, IIT, Northwestern University.
The two newly announced institutes bring the total number of TRIPODS Phase II Institutes to four. Previous TRIPODS Institutes were announced in 2020, including collaborations between several universities.
