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NSF Launches Multidisciplinary Data Science Program for Collaborative Institutes

1 November 2016 218 views No Comment

The National Science Foundation (NSF) announced Transdisciplinary Research in Principles of Data Science (TRIPODS), a new crosscutting solicitation, in late September. Sponsored by both the Mathematical and Physical Science (MPS) and the Computer and Information Science and Engineering (CISE) directorates, TRIPODS, according to the solicitation, “aims to bring together the statistics, mathematics, and theoretical computer science communities to develop the theoretical foundations of data science through integrated research and training activities.” The program is part of Harnessing Data for 21st Century Science and Engineering, one of the 10 big ideas for future NSF investments announced this past spring.

The solicitation was informed by an April 2016 workshop, “Theoretical Foundations of Data Science,” attended by 43 people. The statisticians among them included Amy Braverman, David Donoho, David Dunson, Xiaming Huo, and Bin Yu. A key conclusion of the report is that “theoretical foundations are necessary in all aspects of data science, from the generation and collection of data to the analysis and decision making processes.”

The program will have two phases. Phase I will support the development of small collaborative institutes that have significant and integral participation of the statistics, mathematics, and theoretical computer science communities. Phase II, to be announced at a later date (pending funding), will “support a smaller number of larger institutes selected from the Phase I institutes via a second competitive proposal process.”
The total anticipated funding amount is $12 million, with eight to 10 awards expected to be given. The awards would be funded for up to $500,000 per year for a duration of three years.

Letters of intent are due January 19, 2017. The proposal submission window is March 1–15. Statistics Program Director Nandini Kannan is one of five TRIPODS contacts.

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