Opportunity Information: Apply for 16 615
Apply for 16 615
- The National Science Foundation in the science and technology and other research and development sector is offering a public funding opportunity titled "Transdisciplinary Research in Principles of Data Science" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 47.049, 47.070.
- This funding opportunity was created on Sep 28, 2016.
- Applicants must submit their applications by Mar 15, 2017. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $1,500,000.00 in funding.
- The number of recipients for this funding is limited to 10 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Opportunity Summary:
The Transdisciplinary Research in Principles of Data Science (TRIPODS) grant opportunity is a National Science Foundation (NSF) program designed to strengthen the theoretical and mathematical underpinnings of data science by intentionally bridging three core research communities: statistics, mathematics, and theoretical computer science. The central idea is that many of the hardest and most enduring questions in data science (for example, questions about learning, inference, optimization, uncertainty, generalization, robustness, privacy, and algorithmic limits) cannot be fully addressed within a single discipline. TRIPODS therefore supports integrated research and training activities that are built from the start to be genuinely cross-cutting, rather than loosely collaborative or siloed.
This solicitation describes TRIPODS Phase I, which focuses on establishing small, collaborative “Institutes.†These Phase I Institutes are meant to function as hubs that organize and accelerate foundational research while also developing researchers through coordinated training efforts. The program emphasizes that participation from statistics, mathematics, and theoretical computer science must be significant and integral, meaning proposals should not treat one of the fields as merely a supporting role. Instead, the Institute’s research agenda, educational components, and collaborative structure should reflect true transdisciplinary engagement, with each community shaping the questions being asked and the methods being developed.
TRIPODS is structured as a two-phase program. Phase I awards support the formation and early development of multiple small Institutes. Phase II, which is anticipated to be described in a future solicitation (and is subject to available funds), is expected to fund a smaller number of larger Institutes. Importantly, Phase II Institutes would be selected through a second competitive proposal process that draws from the pool of Phase I awardees. In practice, this means Phase I can be seen as both a launch point for building an Institute and a proving ground for demonstrating the Institute’s ability to deliver strong, integrated research and training outcomes at a larger scale.
From the funding details provided, the opportunity is an NSF discretionary grant in the Science and Technology and other Research and Development category. The funding opportunity number is 16-615, and the CFDA numbers listed are 47.049 and 47.070. The award ceiling is $1,500,000, with an expected 10 awards under this Phase I solicitation. The original closing date for proposals was March 15, 2017, and the opportunity was created on September 28, 2016. Eligibility is listed broadly as “Others,†with further clarification referenced in an additional eligibility text field (not included in the excerpt), which typically signals that applicants should consult the full solicitation for specifics on which organizations or institutional types may apply and under what conditions.
Overall, TRIPODS Phase I is aimed at building focused, multi-community Institutes that push forward the core principles of data science and train researchers who can operate fluently across statistics, mathematics, and theoretical computer science. The program’s defining feature is that it funds foundational work and community-building together, with the expectation that successful Phase I Institutes may later compete to scale into larger Phase II Institutes if NSF releases that subsequent competition and funding is available.
TRIPODS (Transdisciplinary Research in Principles of Data Science) Phase I - FAQs
1) What is the TRIPODS program?
TRIPODS (Transdisciplinary Research in Principles of Data Science) is a National Science Foundation (NSF) program focused on strengthening the theoretical and mathematical foundations of data science by intentionally bridging three research communities: statistics, mathematics, and theoretical computer science.
2) What problem is TRIPODS trying to address?
The program is built around the idea that many long-standing data science questions cannot be fully solved within a single discipline. TRIPODS targets foundational questions such as learning, inference, optimization, uncertainty, generalization, robustness, privacy, and algorithmic limits, with an emphasis on approaches that are genuinely cross-cutting across the three core fields.
3) What does “transdisciplinary†mean in the context of TRIPODS?
In TRIPODS, transdisciplinary means the research and training are integrated from the start across statistics, mathematics, and theoretical computer science. Proposals are expected to avoid siloed work or arrangements where one field is only a minor supporting role. Instead, all three communities should meaningfully shape the research agenda, methods, educational activities, and collaboration structure.
4) What is TRIPODS Phase I?
Phase I is the part of the program described in this solicitation, focused on establishing small, collaborative Institutes. These Institutes are intended to function as hubs that organize and accelerate foundational research in data science principles while also developing researchers through coordinated training efforts.
5) What is an “Institute†under TRIPODS Phase I?
A TRIPODS Phase I Institute is a small, collaborative hub designed to support both (1) foundational, cross-community research on the principles of data science and (2) coordinated training activities that help develop researchers who can work fluently across statistics, mathematics, and theoretical computer science.
6) What kinds of activities does Phase I support?
Based on the description provided, Phase I supports integrated research and training activities that accelerate foundational work while building community and developing researchers. The Institute model emphasizes organizing and coordinating efforts rather than running loosely connected projects.
7) Which research communities must be represented in a TRIPODS proposal?
Participation from statistics, mathematics, and theoretical computer science must be significant and integral. The solicitation emphasizes that proposals should not treat any of these areas as merely supportive; each should play a central role in shaping the Institute’s research and training agenda.
8) What topics does TRIPODS consider part of the “principles of data science�
The description highlights foundational issues such as learning, inference, optimization, uncertainty, generalization, robustness, privacy, and algorithmic limits, and it frames these as examples of enduring questions that benefit from deep theoretical and mathematical work spanning multiple fields.
9) How is TRIPODS structured overall?
TRIPODS is described as a two-phase program. Phase I funds multiple small Institutes to launch and develop early results and training. Phase II is anticipated to be described in a future solicitation (subject to available funds) and is expected to fund a smaller number of larger Institutes.
10) Does receiving a Phase I award automatically lead to Phase II funding?
No. Phase II Institutes are expected to be selected through a second competitive proposal process, drawing from the pool of Phase I awardees. Phase I can be viewed as a launch point and a proving ground, but it does not guarantee Phase II funding.
11) Who can apply for TRIPODS Phase I?
Eligibility is listed broadly as “Others,†with additional clarification referenced in an additional eligibility text field that is not included in the excerpt. This typically indicates applicants should consult the full solicitation for the specific organizational or institutional eligibility requirements and any conditions that may apply.
12) What type of grant is this?
This opportunity is described as an NSF discretionary grant in the “Science and Technology and other Research and Development†category.
13) What is the funding opportunity number?
The funding opportunity number is 16-615.
14) What CFDA numbers are associated with this opportunity?
The CFDA numbers listed are 47.049 and 47.070.
15) What is the maximum award amount (award ceiling) for Phase I?
The award ceiling listed for this Phase I solicitation is $1,500,000.
16) How many awards were expected under Phase I?
The solicitation states an expectation of 10 awards under this Phase I opportunity.
17) What were the key dates for this opportunity?
The opportunity was created on September 28, 2016, and the original closing date for proposals was March 15, 2017.
18) What is the main goal of TRIPODS Phase I?
The core goal is to build focused Institutes that push forward foundational research in data science principles while simultaneously training researchers to operate across statistics, mathematics, and theoretical computer science, with strong, integrated community-building as a defining feature.
19) Why does TRIPODS emphasize community-building and training along with research?
The program description frames foundational progress in data science as requiring both deep theory and a sustained, integrated community. TRIPODS therefore supports Institutes that combine research with coordinated training to develop researchers who can work effectively across the three core fields.
20) How should proposals treat collaboration across disciplines?
The solicitation emphasizes that collaboration should be built from the start to be genuinely cross-cutting. It discourages loosely collaborative or siloed structures and expects that the Institute’s agenda and activities reflect real integration among statistics, mathematics, and theoretical computer science.
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