Projects Span AI Applications to HEP to Studies of fundamental AI Techniques for Analysis and Discovery
WASHINGTON, D.C. - Today, the U.S. Department of Energy (DOE) announced $4.3 million in funding for 16 projects in artificial intelligence (AI) research for high energy physics (HEP). These awards support the DOE Office of Science initiative in artificial intelligence research to use AI techniques to deliver scientific discoveries that would not otherwise be possible, and to broaden participation in high energy physics research.
“AI and Machine Learning (ML) techniques in high energy physics are vitally important for advancing the field,” said Gina Rameika, DOE Associate Director of Science for High Energy Physics. “These awards represent new opportunities for university researchers that will enable the next discoveries in high energy physics.”
Funded projects include constructing models to increase the speed of simulations for cosmology and particle physics; the use of deep learning to develop governing theories; and ML techniques to efficiently and thoroughly search the parameter spaces of likely new theories of particle physics that have their origins at the highest energy scales. These investments also include development of new methods for machine learning in real-time (known as edge computing) for data collection and efforts toward performing robust data analysis with self-consistent ML measurement techniques.
This announcement for seed awards to universities comes on the heels of a similar announcement for team awards to the national laboratories for the same Funding Opportunity Announcement: Artificial Intelligence Research for High Energy Physics DE-FOA-0002705. The projects were selected by competitive peer review.
Total funding is $4.3 million for projects lasting up to three years in duration, with $1.3 million in the first budget period. The list of projects and more information can be found here.