Former PPPL intern honored for outstanding machine learning poster


The American Physical Society (APS) has recognized a summer intern at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) for producing an outstanding research poster at the world-wide APS Division of Plasma Physics (DPP) gathering last October. The student, Marco Miller, a senior at Columbia University majoring in applied physics, used machine learning to accelerate a leading PPPL computer code known as XGC as a participant in the DOE's Summer Undergraduate Laboratory Internship (SULI) program in 2019. The modifications, which will enable the XGC code to calculate more quickly, could help expand the physics included in detailed simulations of the plasma that fuels fusion reactions. The poster, prepared under the mentorship of PPPL physicist Michael Churchill, showed how Miller used machine learning techniques in his research and was presented at the APS-DPP conference in Fort Lauderdale, Florida. "It felt great to get the award," Miller said.