Open AccessThe NSF Convergence Accelerator Program
Author(s) -
Chaitanya Baru,
Lara Campbell,
Aurali Dade,
Pradeep Fulay,
Alex Loewi,
Douglas Maughan,
Ibrahim Mohedas,
Linda Molnar,
Michael Pozmantier,
Michael Reksulak,
Shelby Smith,
Nicole Tehrani
Publication year - 2022
Publication title -
the ai magazine/ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v43i1.19118
Subject(s) - convergence (economics) , mentorship , curriculum , computer science , engineering management , research program , track (disk drive) , engineering , political science , pedagogy , sociology , law , economics , economic growth , operating system , philosophy , epistemology
The National Science Foundation's Convergence Accelerator is a unique program offering researchers and innovators the opportunity to translate research results into tangible solutions that make a difference for society. Through an intense innovation curriculum and a mentorship program, researchers gain skills and experiences that are of use not only during this program but throughout their careers. This article describes the NSF Convergence Accelerator program and its initial funded convergence research topics—or “tracks”—funded in 2019 and 2020. In almost every track and NSF-funded project, artificial intelligence and machine learning (AI/ML) approaches and methods are playing an essential role.