Raspberry Simpson

Degree: Ph.D. from the Massachusetts Institute of Technology
Research: Plasma Physics  
Joined LLNL: October 2022

Research at LLNL: Raspberry works on developing new experimental and machine learning tools to optimize laser-driven secondary particle sources. Several high-repetition rate lasers that can fire many times per second are being built around the world, enabling growth in the rate of scientific discovery. Raspberry’s work aims to address the need for next-generation diagnostics, machine learning methods, and analysis tools to be able perform laser experiments at faster rates. The focus of her Lawrence Fellow project is developing a new methodology based on representation learning to integrate heterogeneous data to constrain parameters that are not directly measurable in laser-driven particle experiments towards the goal of optimizing and tailoring laser-driven particle sources.

Bio: Raspberry Simpson is a Lawrence Fellow in the National Ignition Facility/Photon Science Directorate. Prior to joining LLNL in 2022, she earned her Ph.D. in Nuclear Engineering with a focus on Plasma Physics from the Massachusetts Institute of Technology. She completed most of her Ph.D. research at LLNL under the direction of Dr. Tammy Ma, focusing on the investigation of laser-driven particle acceleration for the development of tunable ion sources for applications in high energy density science. Before beginning her graduate studies, Raspberry worked in the Physics Division at Los Alamos National Laboratory in Los Alamos, New Mexico, developing neutron imaging diagnostics for inertial confinement fusion experiments and electron radiography for material science studies. She received her undergraduate degree at Columbia University in Applied Physics and is a recipient of the National Science Foundation Graduate Research Fellowship and NNSA’s Laboratory Residency Graduate Fellowship.