Kayla DeHolton

Kayla Leonard DeHolton is a particle physicist whose primary research interests are the phenomenon of neutrino oscillations and applications of machine learning in neutrino detection. She is currently a postdoctoral researcher at Penn State university and a fellow at the Institute for Gravitation and the Cosmos. She is co-convener of the Oscillations Working Group for the IceCube experiment.

Neutrinos are one of the most abundant known particles in the Universe, yet they are one of the least well understood.  Her primary work is measuring the properties of neutrinos, through a phenomenon known as "Neutrino Oscillations" using the IceCube Neutrino Observatory located at the South Pole. Her current research activities include analyzing data from IceCube DeepCore and preparing for the IceCube Upgrade which will be deployed in 2025-26. She also contributes to GraphNeT, an open-source deep learning framework for neutrino telescopes, and Eos, a small R&D testbed for hybrid detection of Chernkov and scintillation light.

Education

PhD in Physics,  MA in Physics
University of Wisconsin--Madison

BS in Physics, BS in Astronomy
The University of Texas at Austin