Dani Ushizima and Berkeley Lab machine-learning team receive the ALS' 2021 Halbach Award

September 28, 2021

BIDS Research Affiliate Dani Ushizima, together with a team of physicists at Berkeley Lab, received the ALS’ 2021 Klaus Halbach Award for Innovative Instrumentation for their development of a machine-learning-based application to stabilize the transverse beam size and enhance the photon-beam performance at Berkeley Lab Advanced Light Source. The team used machine-learning techniques to solve a problem that has plagued third-generation light sources for a long time: fluctuations in beam size due to the motion of insertion devices. By improving the stability of the electron beam, the project successfully enhanced the performance of the ALS.

2021 Halbach Award winnersThe team included a Simon Leemann, Alex Hexemer, Shuai Liu, Yuping Lu, C. Nathan Melton, Hiroshi Nishimura, Changchun Sun.

“This sort of work is emblematic of what is needed,” said Ushizima, “close cooperation between domain experts and data scientists, customizing and tailoring techniques to take advantage of scientific information to bring new levels of sophistication to machine-learning methods.”

Machine-Learning Team Receives 2021 Halbach Award
August 30, 2021  |   Lori Tamura   |   LBL ALS News

Featured Fellows

Daniela Ushizima

Computational Research Division, CAMERA, LBNL
Research Affiliate