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NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Synopsis

This program seeks to accelerate fundamental, broad-based research on wireless-specific machine learning (ML) techniques, towards a new wireless system and architecture design, which can dynamically access shared spectrum, efficiently operate with limited radio and network resources, and scale to address the diverse and stringent quality-of-service requirements of future wireless applications. In parallel, this program also targets research on reliable distributed ML by addressing the challenge of computation over wireless edge networks to enable ML for wireless and future applications. Model-based approaches for designing the wireless network stack have proven quite efficient in delivering the networks in wide use today; research enabled by this program is expected to identify realistic problems that can be best solved by ML and to address fundamental questions about expected improvements from using ML over model-based methods.

Proposals may address one or more Research Vectors (RVs): ML for Wireless Networks; ML for Spectrum Management; and Distributed ML over Wireless Edge Networks. It is anticipated that 10 to 15 awards will be made, with an award size of $300,000-$1,500,000, for periods of up to 3 years. The budget should be commensurate with the complexity of the proposed research. Projects will be funded across this range.

Program contacts

Alexander Sprintson
Program Director, CISE/CNS
asprints@nsf.gov (703) 292-2170
Balakrishnan Prabhakaran
Program Director, CISE/IIS
bprabhak@nsf.gov 703-292-4847
Phillip A. Regalia
Program Director, CISE/CCF
pregalia@nsf.gov (703) 292-2981 CISE/CCF
Anthony Kuh
Program Director, ENG/ECCS
akuh@nsf.gov (703) 292-2210 ENG/ECCS
Jenshan Lin
Program Director, ENG/ECCS
jenlin@nsf.gov 703-292-7950 ENG/ECCS
Vida Ilderem
Center Executive Sponsor, Vice President, Intel Labs
vida.ilderem@intel.com (503) 712-5740
Shilpa Talwar
Senior Principal Engineer, Intel Labs
shilpa.talwar@intel.com (408) 785-6151
Nageen Himayat
Principal Engineer, Intel Labs
nageen.himayat@intel.com (408) 765-5043
Jeff Parkhurst
Center Program Director, Intel Labs
jeff.parkhurst@intel.com (916) 356-2508

Awards made through this program

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Map of recent awards made through this program