A.I. and Machine Learning

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March 24, 2021
News Brief
New machine learning tool diagnoses electron beams in an efficient, non-invasive way
It can help operators optimize the performance of X-ray lasers, electron microscopes, medical accelerators and other devices that depend on high-quality beams.
Virtual Diagnostics
March 8, 2021
Press Release
In a leap for battery research, machine learning gets scientific smarts
The latest advance from a research collaboration with industry could dramatically accelerate the development of sturdier batteries for fast-charging electric vehicles.
Diagram with icons depicting how X-ray studies, machine learning and lab work (left) were used to study electrode nanoparticles (center) for batteries used in electric vehicles, consumer electronics and solar power (right)
November 24, 2020
News Feature
Researchers search uncharted waters to find a better data-storage material
Most new materials are discovered near the proverbial shore. Now, scientists deploy artificial intelligence and high-throughput experimental techniques to search previously uncharted waters to find revolutionary new materials.
A ship sails along a coastline, while a sea monster swims near an island where treasure can be found.
September 30, 2020
News Feature
Q&A: How machine learning helps scientists hunt for particles, wrangle floppy proteins and speed discovery
Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.
Daniel Ratner
August 25, 2020
News Feature
Auralee Edelen and Wai Ling Wu receive 2020 Panofsky Fellowships at SLAC
Their work uses machine learning to transform the way scientists tune particle accelerators for experiments and solve longstanding mysteries in astrophysics and cosmology.
Portraits of Auralee Edelen and Kimmy Wu
June 23, 2020
News Feature
SLAC’s Amy Cordones-Hahn and Brendan O’Shea receive DOE Early Career Awards
The prestigious awards provide at least $2.5 million over five years in support of their work in understanding photochemical reactions and improving accelerator beams.
SLAC staff scientists Amy Cordones-Hahn and Brendan O'Shea
April 29, 2020
News Feature
A new machine learning method streamlines particle accelerator operations
It combines human knowledge and expertise with the speed and efficiency of “smart” computer algorithms.
Accelerator Control Room
April 16, 2020
News Feature
SLAC joins the global fight against COVID-19
The lab is responding to the coronavirus crisis by imaging disease-related biomolecules, developing standards for reliable coronavirus testing and enabling other essential research.
SARS-CoV-2
June 25, 2019
News Feature
Symmetry: The future of particle accelerators may be autonomous
Particle accelerators are some of the most complicated machines in science.
October 16, 2018
News Feature
Symmetry: Studying the stars with machine learning
To keep up with an impending astronomical increase in data about our universe, astrophysicists turn to machine learning.

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