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New research at the Facility for Rare Isotope Beams at Michigan State University will harness the power of machine learning to accelerate nuclear science.
September 15, 2023
The Facility for Rare Isotope Beams, or FRIB, at Michigan State University is home to a world-unique particle accelerator designed to push the boundaries of our understanding of nature. Now, FRIB is accelerating that work with a form of artificial intelligence known as machine learning with support from the Office of Nuclear Physics and the Office of High Energy Physics at the U.S. Department of Energy Office of Science. FRIB scientists have received several grants that aim to bring machine learning’s power to process immense data sets to bear in experiments, theoretical studies and the science and engineering that keeps the accelerator humming.
Machine learning has the promise to accelerate research in STEM fields, but this will require people with unique training and expertise. MSU has won a nearly $3 million NSF grant to help prepare that next-generation workforce. This image was created by the DALL·E 2 AI system.
December 13, 2022
The National Science Foundation (NSF) has awarded MSU nearly $3 million to create a graduate program that will help usher in a new era of STEM discoveries using the power of machine learning. Project leader Daniel Appelö and his team are working with the NSF to ensure the United States can maintain its leadership in the machine learning space — especially in science, technology, engineering and math applications — for generations to come.
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April 29, 2021
MSU computational biologist Arjun Krishnan is the recipient of a 5-year, $704,889 NSF Early CAREER Award to develop machine learning approaches that will automatically annotate publicly available samples from human and major animal models on a massive scale. His efforts will allow researchers to seamlessly search and re-analyze immense reserves of untapped omics data for advances in biology and human health. The award will also support Krishnan’s efforts to help students interested in programming and data science gain access to the “hidden curriculum” of bioinformatics.

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