Mathematical Foundations of Artificial Intelligence Research

Mathematical Foundations of Artificial Intelligence Research is sponsored by Not explicitly stated (listed on The Grant Portal as a research funding opportunity). This research funding opportunity supports nonprofit academic organizations, research institutions, and eligible U. S.

-based organizations conducting interdisciplinary research on mathematical and theoretical foundations for sustainable, trustworthy, and socially responsible AI.

NSF 24-569: Mathematical Foundations of Artificial Intelligence (MFAI) | NSF - U.S. National Science Foundation Active funding opportunity This document is the current version. Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .

All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects. NSF 24-569: Mathematical Foundations of Artificial Intelligence To save a PDF of this solicitation, select Print to PDF in your browser's print options.

Program Solicitation NSF 24-569 National Science Foundation Directorate for Mathematical and Physical Sciences Division of Mathematical Sciences Directorate for Computer and Information Science and Engineering Division of Computing and Communication Foundations Division of Information and Intelligent Systems Directorate for Engineering Division of Civil, Mechanical and Manufacturing Innovation Division of Electrical, Communications and Cyber Systems Directorate for Social, Behavioral and Economic Sciences Division of Social and Economic Sciences Full Proposal Deadline(s) (due by 5 p.

m. submitting organization's local time): Important Information And Revision Notes Any proposal submitted in response to this solicitation should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted.

The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable version of the PAPPG. Submitting a proposal prior to a specified deadline does not negate this requirement.

Summary Of Program Requirements Mathematical Foundations of Artificial Intelligence (MFAI) Machine Learning and Artificial Intelligence (AI) are enabling extraordinary scientific breakthroughs in fields ranging from protein folding, natural language processing, drug synthesis, and recommender systems to the discovery of novel engineering materials and products.

These achievements lie at the confluence of mathematics, statistics, engineering and computer science, yet a clear explanation of the remarkable power and also the limitations of such AI systems has eluded scientists from all disciplines. Critical foundational gaps remain that, if not properly addressed, will soon limit advances in machine learning, curbing progress in artificial intelligence.

It appears increasingly unlikely that these critical gaps can be surmounted with increased computational power and experimentation alone. Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet the future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE) will jointly sponsor research collaborations consisting of mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists focused on the mathematical and theoretical foundations of AI.

Research activities should focus on the most challenging mathematical and theoretical questions aimed at understanding the capabilities, limitations, and emerging properties of AI methods as well as the development of novel, and mathematically grounded, design and analysis principles for the current and next generation of AI approaches.

Specific research goals include: establishing a fundamental mathematical understanding of the factors determining the capabilities and limitations of current and emerging generations of AI systems, including, but not limited to, foundation models, generative models, deep learning, statistical learning, federated learning, and other evolving paradigms; the development of mathematically grounded design and analysis principles for the current and next generations of AI systems; rigorous approaches for characterizing and validating machine learning algorithms and their predictions; research enabling provably reliable, translational, general-purpose AI systems and algorithms; encouragement of new collaborations in this interdisciplinary research community and between institutions.

The overall goal is to establish innovative and principled design and analysis approaches for AI technology using creative yet theoretically grounded mathematical and statistical frameworks, yielding explainable and interpretable models that can enable sustainable, socially responsible, and trustworthy AI. Cognizant Program Officer(s): Please note that the following information is current at the time of publishing.

See program website for any updates to the points of contact. Stacey Levine, Program Director, MPS/DMS, telephone: (703) 292-2948, email: mfai@nsf. gov Eyad Abed, Program Director, ENG/ECCS, telephone: (703) 292-2303, email: mfai@nsf.

gov Yulia Gel, Program Director, MPS/DMS, telephone: (703) 292-7888, email: mfai@nsf. gov Alfred Hero, Program Director, CISE/CCF, telephone: (703) 292-8910, email: Anthony Kuh, Program Director, ENG/ECCS, telephone: (703) 292-4714, email: mfai@nsf. gov Tracy J.

Kimbrel, telephone: (703) 292-8910, email: mfai@nsf. gov Phillip A. Regalia, Program Director, CISE/CCF, telephone: (703) 292-2981, email: mfai@nsf.

gov Christopher W. Stark, Program Director, MPS/DMS, telephone: (703) 292-4869, email: mfai@nsf. gov Reha M.

Uzsoy, Program Director, ENG/CMMI, telephone: (703) 292-2681, email: mfai@nsf. gov Juan P. Wachs, Program Director, CISE/IIS, telephone: (703) 292-8714, email: mfai@nsf.

gov Kenneth C. Whang, Program Director, CISE/IIS, telephone: (703) 292-5149, email: mfai@nsf. gov Joseph M.

Whitmeyer, Program Director, SBE/SES, telephone: (703) 292-7808, email: mfai@nsf. gov Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s): 47. 049 --- Mathematical and Physical Sciences 47.

070 --- Computer and Information Science and Engineering 47. 075 --- Social Behavioral and Economic Sciences Anticipated Type of Award: Standard Grant or Continuing Grant Estimated Number of Awards: 15 We anticipate making up to 15 awards in each competition. Each award size may vary and is expected to range from $500k to $1.

5M total. Each award is expected to take place for a duration of 36 months. Award size is contingent upon the scope, scale and complexity of the proposed project.

The number of awards will be subject to the availability of funds and quality of proposals received. Anticipated Funding Amount: $8,500,000 Up to $8,500,000 per year is expected for new awards, subject to availability of funds and receipt of meritorious proposals.

Who May Submit Proposals: Proposals may only be submitted by the following: Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.

Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members.

As of the date the proposal is submitted, any PI, co-PI, or senior/key personnel must hold either: a tenured or tenure-track position, or a primary, full-time, paid appointment in a research or teaching position at a US-based campus of an organization eligible to submit to this solicitation (see above), with exceptions granted for family or medical leave, as determined by the submitting organization.

Individuals with primary appointments at for-profit non-academic organizations or at overseas branch campuses of U.S. institutions of higher education are not eligible. Limit on Number of Proposals per Organization: There are no restrictions or limits.

Limit on Number of Proposals per PI or co-PI: 1 A Principal Investigator (PI) or co-Principal Investigator (co-PI) can be part of no more than one proposal per deadline in response to this solicitation. Proposal Preparation and Submission Instructions A. Proposal Preparation Instructions Letters of Intent: Not required Preliminary Proposal Submission: Not required Full Proposals submitted via Research.

gov: NSF Proposal and Award Policies and Procedures Guide (PAPPG) guidelines apply. The complete text of the PAPPG is available electronically on the NSF website at: https://www. nsf.

gov/publications/pub_summ. jsp? ods_key=pappg .

Full Proposals submitted via Grants. gov: NSF Grants. gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.

gov guidelines apply (Note: The NSF Grants. gov Application Guide is available on the Grants. gov website and on the NSF website at: https://www.

nsf. gov/publications/pub_summ. jsp?

ods_key=grantsgovguide ). Cost Sharing Requirements: Inclusion of voluntary committed cost sharing is prohibited. Indirect Cost (F&A) Limitations: Other Budgetary Limitations: Full Proposal Deadline(s) (due by 5 p.

m. submitting organization's local time): Proposal Review Information Criteria National Science Board approved criteria. Additional merit review criteria apply.

Please see the full text of this solicitation for further information. Award Administration Information Standard NSF award conditions apply. Standard NSF reporting requirements apply.

Machine Learning and Artificial Intelligence (AI) are enabling extraordinary scientific breakthroughs in fields ranging from protein folding, natural language processing, drug synthesis, and recommender systems to the discovery of novel engineering materials and products.

While these achievements lie at the confluence of mathematics, statistics, engineering, and computer science, a clear explanation of the remarkable power and limitations of such AI systems has eluded scientists from all disciplines. Critical foundational gaps remain that, if not properly addressed, will soon limit advances in machine learning, curbing progress in artificial intelligence.

It appears increasingly unlikely that these critical gaps can be surmounted with increased computational power and experimentation alone. Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology.

NSF's previous investments in the Mathematical and Scientific Foundations of Deep Learning (MoDL) program ( NSF 20-540 ), the Stimulating Collaborative Advances Leveraging Expertise in the Mathematical and Scientific Foundations of Deep Learning (SCALE MoDL) program ( NSF 21-561 ), the TRIPODS program ( NSF 19-604 ), Harnessing the Data Revolution, and the Foundations of Machine Learning theme within the AI Institutes ( NSF 20-503 ) have yielded important advances in understanding the mathematical, scientific, and theoretical foundations of deep learning, machine learning, and data science.

Still, the tremendous body of AI knowledge and practice currently rests on a surprisingly limited mathematical foundation. Untapped and under-explored mathematical constructs have the potential to provide paradigm-changing approaches leading to more accurate, more robust, and less data- and computationally-hungry approaches.

MFAI aims to support research focused on the most challenging theoretical questions aimed at understanding the capabilities, limitations, and emerging properties of AI methods as well as the development of novel, mathematically grounded design and analysis principles for the current and next generations of AI.

PI teams should collectively possess appropriate expertise drawn from mathematics/statistics, computer science, engineering, and social and behavioral sciences, as appropriate to the project.

The scientific focus must be on the mathematical and theoretical foundations, but relevance to application domains where the mathematical advances may lead to significantly new capabilities or a deeper understanding of existing empirical observations should be addressed. Collaboration between theoretical and empirical scientists is highly encouraged.

Specific research goals are: A fundamental mathematical understanding of the factors determining the capabilities and limitations of current and emerging AI systems, including, but not limited to, foundation models, generative models, deep learning, statistical learning, federated learning, and other evolving paradigms; The development of mathematically grounded design and analysis principles for the current and next generations of AI; Rigorous approaches for characterizing and validating machine learning algorithms and their predictions, as well as research enabling provably reliable, translational, general-purpose AI systems and algorithms; Encouragement of new collaborations across this interdisciplinary research community and between institutions.

Opportunities for advancing the mathematical foundations of modern AI include, but are not limited to, statistical inference and methodology, formal and symbolic logic, topology, complexity theory, algebraic geometry, representation theory, and analysis approaches such as dynamical systems, partial differential equations, mean field theory, approximation theory, and optimization theory, which, in turn, could facilitate the interpretability, transferability, generalizability, and scalability of AI.

Successful proposals will describe an actionable approach for advancing the mathematical and theoretical foundations of the current and/or next generation of artificial intelligence methodologies through targeting at least one key technical obstacle. Successful proposals will also make clear the innovative mathematical and theoretical contributions that will be addressed in the project.

Proposals should clearly articulate the challenges to be addressed, the technical approaches to be taken to address these challenges, and discuss why the proposed technical approaches are viable, along with alternative approaches that might be adopted in the event of negative outcomes.

Each proposal must clearly demonstrate substantial collaborative contributions from team members with complementary expertise and should highlight how the complementary expertise of the team provides a unique opportunity for progress. Each project team should also contribute to the development of the multidisciplinary research workforce that will continue to advance the field in the future.

This will be through the research involvement of students, and/or postdoctoral associates from across the multi-disciplinary spectrum of relevant areas. One or more award participants, including the project Principal Investigator (PI), will be expected to attend a PI meeting each year of the award to exchange ideas, effective practices, assessment strategies, as well as challenges.

Anticipated Type of Award: Continuing Grant or Standard Grant Estimated Number of Awards: up to 15 We anticipate making up to 15 awards in each competition. Each award size may vary and is expected to range from $500k to $1. 5M total.

Each award is expected to take place for a duration of 36 months. Award size is contingent upon the scope, scale and complexity of the proposed project. The number of awards will be subject to the availability of funds and quality of proposals received.

Anticipated Funding Amount: $8,500,000 Up to $8,500,000 per year is expected for new awards, subject to availability of funds and receipt of meritorious proposals. IV.

Eligibility Information Who May Submit Proposals: Proposals may only be submitted by the following: Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities.

Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members.

As of the date the proposal is submitted, any PI, co-PI, or senior/key personnel must hold either: a tenured or tenure-track position, or a primary, full-time, paid appointment in a research or teaching position at a US-based campus of an organization eligible to submit to this solicitation (see above), with exceptions granted for family or medical leave, as determined by the submitting organization.

Individuals with primary appointments at for-profit non-academic organizations or at overseas branch campuses of U.S. institutions of higher education are not eligible. Limit on Number of Proposals per Organization: There are no restrictions or limits.

Limit on Number of Proposals per PI or co-PI: 1 A Principal Investigator (PI) or co-Principal Investigator (co-PI) can be part of no more than one proposal per deadline in response to this solicitation. V. Proposal Preparation And Submission Instructions A.

Proposal Preparation Instructions Full Proposal Preparation Instructions : Proposers may opt to submit proposals in response to this Program Solicitation via Research. gov or Grants. gov. Full Proposals submitted via Research.

gov: Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Proposal and Award Policies and Procedures Guide (PAPPG). The complete text of the PAPPG is available electronically on the NSF website at: https://www. nsf.

gov/publications/pub_summ. jsp? ods_key=pappg .

Paper copies of the PAPPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from nsfpubs@nsf. gov . The Prepare New Proposal setup will prompt you for the program solicitation number.

Full proposals submitted via Grants. gov: Proposals submitted in response to this program solicitation via Grants. gov should be prepared and submitted in accordance with the NSF Grants.

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To obtain copies of the Application Guide and Application Forms Package, click on the Apply tab on the Grants. gov site, then click on the Apply Step 1: Download a Grant Application Package and Application Instructions link and enter the funding opportunity number, (the program solicitation number without the NSF prefix) and press the Download Package button. Paper copies of the Grants.

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All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via Research. gov. PAPPG Chapter II. E.

3 provides additional information on collaborative proposals. See PAPPG Chapter II. D.

2 for guidance on the required sections of a full research proposal submitted to NSF. Please note that the proposal preparation instructions provided in this program solicitation may deviate from the PAPPG instructions. Title : To facilitate timely processing, the title of the proposed project should begin with " MFAI: ".

When you submit a proposal as part of a set of collaborative proposals, the title of the proposal should begin with " Collaborative Research: MFAI: " Please note that if submitting via Research. gov, the system will automatically insert the prepended title "Collaborative Research" when the collaborative set of proposals is created.

All proposals in a group of separately submitted collaborative proposals should have the same title and should be submitted to the MFAI program.

Supplementary Documentation : Since the success of collaborative research efforts is known to depend on thoughtful coordination mechanisms that regularly bring together the various participants of the project, a Collaboration Plan is required, even when the investigators are affiliated with the same institution. Up to two pages are allowed for Collaboration Plans and they must be submitted as a document under Supplementary Documents.

The length and level of detail provided in the Collaboration Plan should be commensurate with the complexity of the proposed project. Collaboration Plans and proposed budgets should demonstrate that key personnel, and especially lead PIs, have allocated adequate time for both their individual technical contributions and the leadership of collaborative activities necessary to realize the synergistic effects of multidisciplinary research.

Inclusion of voluntary committed cost sharing is prohibited. Budget Preparation Instructions: All proposals are required to include as a line item in their budgets, the travel expenses associated with participation in the yearly PI Meeting. Full Proposal Deadline(s) (due by 5 p.

m. submitting organization's local time): D. Research.

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gov, see detailed technical instructions available at: https://www. research. gov/research-portal/appmanager/base/desktop?

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The Research. gov Help Desk answers general technical questions related to the use of the Research. gov system.

Specific questions related to this program solicitation should be referred to the NSF program staff contact(s) listed in Section VIII of this funding opportunity. For Proposals Submitted Via Grants. gov: Before using Grants.

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The NSF Grants. gov Proposal Processing in Research. gov informational page provides submission guidance to applicants and links to helpful resources including the NSF Grants.

gov Application Guide , Grants. gov Proposal Processing in Research. gov how-to guide , and Grants.

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m. submitting organization's local time on the deadline. Please note that some errors cannot be corrected in Grants.

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gov. After proposers have received an e-mail notification from NSF, Research. gov should be used to check the status of an application. VI.

NSF Proposal Processing And Review Procedures Proposals received by NSF are assigned to the appropriate NSF program for acknowledgement and, if they meet NSF requirements, for review.

All proposals are carefully reviewed by a scientist, engineer, or educator serving as an NSF Program Officer, and usually by three to ten other persons outside NSF either as ad hoc reviewers, panelists, or both, who are experts in the particular fields represented by the proposal. These reviewers are selected by Program Officers charged with oversight of the review process.

Proposers are invited to suggest names of persons they believe are especially well qualified to review the proposal and/or persons they would prefer not review the proposal. These suggestions may serve as one source in the reviewer selection process at the Program Officer's discretion. Submission of such names, however, is optional.

Care is taken to ensure that reviewers have no conflicts of interest with the proposal. In addition, Program Officers may obtain comments from site visits before recommending final action on proposals. Senior NSF staff further review recommendations for awards.

A flowchart that depicts the entire NSF proposal and award process (and associated timeline) is included in PAPPG Exhibit III-1. A comprehensive description of the Foundation's merit review process is available on the NSF website at: https://www. nsf.

gov/bfa/dias/policy/merit_review/ . One of the strategic objectives in support of NSF's mission is to foster integration of research and education through the programs, projects, and activities it supports at academic and research institutions. These institutions must recruit, train, and prepare a diverse STEM workforce to advance the frontiers of science and participate in the U.S. technology-based economy.

NSF's contribution to the national innovation ecosystem is to provide cutting-edge research under the guidance of the Nation's most creative scientists and engineers. NSF also supports development of a strong science, technology, engineering, and mathematics (STEM) workforce by investing in building the knowledge that informs improvements in STEM teaching and learning.

NSF's mission calls for the broadening of opportunities and expanding participation of groups, institutions, and geographic regions that are underrepresented in STEM disciplines, which is essential to the health and vitality of science and engineering. NSF is committed to this principle of diversity and deems it central to the programs, projects, and activities it considers and supports. A.

Merit Review Principles and Criteria The National Science Foundation strives to invest in a robust and diverse portfolio of projects that creates new knowledge and enables breakthroughs in understanding across all areas of science and engineering research and education.

To identify which projects to support, NSF relies on a merit review process that incorporates consideration of both the technical aspects of a proposed project and its potential to contribute more broadly to advancing NSF's mission "to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense; and for other purposes."

NSF makes every effort to conduct a fair, competitive, transparent merit review process for the selection of projects. 1. Merit Review Principles These principles are to be given due diligence by PIs and organizations when preparing proposals and managing projects, by reviewers when reading and evaluating proposals, and by NSF program staff when determining whether or not to recommend proposals for funding and while overseeing awards.

Given that NSF is the primary federal agency charged with nurturing and supporting excellence in basic research and education, the following three principles apply: All NSF projects should be of the highest quality and have the potential to advance, if not transform, the frontiers of knowledge. NSF projects, in the aggregate, should contribute more broadly to achieving societal goals.

These "Broader Impacts" may be accomplished through the research itself, through activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. The project activities may be based on previously established and/or innovative methods and approaches, but in either case must be well justified.

Meaningful assessment and evaluation of NSF funded projects should be based on appropriate metrics, keeping in mind the likely correlation between the effect of broader impacts and the resources provided to implement projects. If the size of the activity is limited, evaluation of that activity in isolation is not likely to be meaningful.

Thus, assessing the effectiveness of these activities may best be done at a higher, more aggregated, level than the individual project. With respect to the third principle, even if assessment of Broader Impacts outcomes for particular projects is done at an aggregated level, PIs are expected to be accountable for carrying out the activities described in the funded project.

Thus, individual projects should include clearly stated goals, specific descriptions of the activities that the PI intends to do, and a plan in place to document the outputs of those activities. These three merit review principles provide the basis for the merit review criteria, as well as a context within which the users of the criteria can better understand their intent.

All NSF proposals are evaluated through use of the two National Science Board approved merit review criteria. In some instances, however, NSF will employ additional criteria as required to highlight the specific objectives of certain programs and activities. The two merit review criteria are listed below.

Both criteria are to be given full consideration during the review and decision-making processes; each criterion is necessary but neither, by itself, is sufficient. Therefore, proposers must fully address both criteria. (PAPPG Chapter II.

D. 2. d(i).

contains additional information for use by proposers in development of the Project Description section of the proposal). Reviewers are strongly encouraged to review the criteria, including PAPPG Chapter II. D.

2. d(i), prior to the review of a proposal. When evaluating NSF proposals, reviewers will be asked to consider what the proposers want to do, why they want to do it, how they plan to do it, how they will know if they succeed, and what benefits could accrue if the project is successful.

These issues apply both to the technical aspects of the proposal and the way in which the project may make broader contributions.

To that end, reviewers will be asked to evaluate all proposals against two criteria: Intellectual Merit: The Intellectual Merit criterion encompasses the potential to advance knowledge; and Broader Impacts: The Broader Impacts criterion encompasses the potential to benefit society and contribute to the achievement of specific, desired societal outcomes.

The following elements should be considered in the review for both criteria: What is the potential for the proposed activity to Advance knowledge and understanding within its own field or across different fields (Intellectual Merit); and Benefit society or advance desired societal outcomes (Broader Impacts)? To what extent do the proposed activities suggest and explore creative, original, or potentially transformative concepts?

Is the plan for carrying out the proposed activities well-reasoned, well-organized, and based on a sound rationale? Does the plan incorporate a mechanism to assess success? How well qualified is the individual, team, or organization to conduct the proposed activities?

Are there adequate resources available to the PI (either at the home organization or through collaborations) to carry out the proposed activities? Broader impacts may be accomplished through the research itself, through the activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project.

NSF values the advancement of scientific knowledge and activities that contribute to achievement of societally relevant outcomes.

Such outcomes include, but are not limited to: full participation of women, persons with disabilities, and other underrepresented groups in science, technology, engineering, and mathematics (STEM); improved STEM education and educator development at any level; increased public scientific literacy and public engagement with science and technology; improved well-being of individuals in society; development of a diverse, globally competitive STEM workforce; increased partnerships between academia, industry, and others; improved national security; increased economic competitiveness of the United States; and enhanced infrastructure for research and education.

Proposers are reminded that reviewers will also be asked to review the Data Management and Sharing Plan and the Mentoring Plan, as appropriate.

Additional Solicitation Specific Review Criteria In addition to the National Science Board merit review criteria, reviewers will be asked to assess how well the proposal addresses the following aspects: Is there is a compelling collaboration plan which clearly articulates the added value and complementary expertise spanning the necessary areas of knowledge?

To what extent does the proposal clearly articulate the mathematical and theoretical innovations? B. Review and Selection Process Proposals submitted in response to this program solicitation will be reviewed by Ad hoc Review and/or Panel Review.

Reviewers will be asked to evaluate proposals using two National Science Board approved merit review criteria and, if applicable, additional program specific criteria. A summary rating and accompanying narrative will generally be completed and submitted by each reviewer and/or panel. The Program Officer assigned to manage the proposal's review will consider the advice of reviewers and will formulate a recommendation.

After scientific, technical and programmatic review and consideration of appropriate factors, the NSF Program Officer recommends to the cognizant Division Director whether the proposal should be declined or recommended for award. NSF strives to be able to tell proposers whether their proposals have been declined or recommended for funding within six months.

Large or particularly complex proposals or proposals from new recipients may require additional review and processing time. The time interval begins on the deadline or