Sam Young

I’m a third year PhD student in the Physics Department at Stanford University, interested in building intelligent systems that can understand and reason about raw, sensor-level data from particle physics experiments. I am advised by Kazu Terao in the neutrino group at SLAC National Accelerator Laboratory, building tools for analyzing data from neutrino detectors.

Sam Young

projects

papers

news

  • Gave a talk on foundation models for neutrino physics at CHEP 2026. Slides
  • Gave a lightning talk on foundation models for neutrino physics at the inaugural HAI + Stanford Data Science conference.
  • Gave a talk on recent work on building a foundation model for neutrino physics at the NPML 2025. Slides
  • Gave a talk on foundation models for neutrino physics at the Machine Learning for Fundamental Physics (ML4FP) summer school. Slides
  • Gave a talk on on foundation models for scientific imaging at the 2025 APS Global Summit.
  • I was awarded the HAI Graduate Fellowship.
  • Gave a talk on differentiable surrogate modeling of optical propagation in LArTPCs at APS April.
  • Won Stanford’s CS 229 Machine Learning’s Best Project Award for my rotation work on pileup synthesis and anomaly detection for the ATLAS experiment.
  • I graduated from Penn with a bachelor’s and master’s in physics, and will continue my studies at Stanford.
  • I’m extremely grateful to receive the Roy and Diana Vagelos Challenge Award (two years full tuition and fees) at Penn.

misc

chroma-cam

chroma-cam

Visualize neutrino detectors in the browser with meshes

Template borrowed from jonbarron.