SLAC Experts

Daniel Ratner

Head of SLAC machine learning initiative

Areas of research: New technologies; machine learning; deep learning; artificial intelligence; accelerator physics; physics and machine learning

Machine learning is changing every facet of what we do at SLAC. It gives us new ideas for how to design and run experiments, and it lets us look at more challenging data and ask tougher physics questions.”

Media contact Machine learning website

News Feature

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

News Feature

The Horizon Prizes celebrate the most exciting, contemporary chemical science at the cutting edge of research and innovation.

News Feature

Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.

News Feature

It combines human knowledge and expertise with the speed and efficiency of “smart” computer algorithms.

News Feature

SLAC researchers say their new method could make it easier to study interactions of ultrabright X-rays with matter

Who we are

SLAC science explained

Vera C. Rubin Observatory LSST

Diversity, Equity & Inclusion

Expecting the Unexpected with AI at Particle Colliders

Daniel Ratner

Taming big data and particle beams: how SLAC researchers are pushing AI to the edge

Molecular movie pioneers awarded the Royal Society of Chemistry's new Horizon Prize

Q&A: How machine learning helps scientists hunt for particles, wrangle floppy proteins and speed discovery

A new machine learning method streamlines particle accelerator operations

Ghostly X-ray images could provide key info for analyzing X-ray laser experiments

Selected stories featuring Daniel Ratner