AI and machine learning

Researchers aim to refine control room tools, improve training, and pave the way for smarter cooperation between humans and machines by studying how operators think and act under pressure.

The microelectronics that power daily life and speed discoveries in science and technology are the focus of a bold new vision to make them more energy efficient and able to operate in extreme environments.

AI is playing a key role in helping SLAC researchers find new galaxies and tiny neutrinos, and discover new drugs.

Researchers across the lab are developing AI tools to harness data and particle beams in real time and make molecular movies, speeding up the discovery process in the era of big data.

SLAC is leading an effort to build a network that will enable AI and machine learning to steer experiments and more.

The prototype DUNE 2x2 detector will capture up to 10,000 neutrino interactions per day.

Digital design engineer Abhilasha Dave’s passion for connecting machine learning and hardware is helping SLAC solve big data challenges.

David Cesar, Julia Gonski and W.L. Kimmy Wu will each receive $2.75 million issued over five years for their research in X-ray and ultrafast science, new physics and primordial gravitational waves.

Charging lithium-ion batteries at high currents just before they leave the factory is 30 times faster and increases battery lifespans by 50%, according to a study at the SLAC-Stanford Battery Center.