Hi, I’m Jordan!

I am a computational scientist with expertise in mathematics, neuroscience, and physics. Currently, I am a postdoctoral researcher in neuroscience at Albert Einstein College of Medicine in New York City, where I study neural function related to sound localization in the auditory system of the barn owl.

I received a Bachelor's of Science in Physics and Mathematics from Seattle University. I received my PhD in computational science from the joint program between San Diego State University and Claremont Graduate University in California. During that program, I was supported by the USDOE Office of Science Graduate Fellowship, working in tandem with the theoretical nuclear physics group at Lawrence Livermore National Laboratory. My dissertation focused on data-driven methods for theoretical nuclear physics: deep learning models for nuclear scattering data, and uncertainty quantification for large-scale calculations in the empirical shell model. After graduation, I worked as a postdoctoral researcher at Argonne National Laboratory, where I developed neural network-based improvemenets for large-scale quantum Monte Carlo simulations.

While at Argonne, I decided to transition from physics into computational neuroscience, and I had the opportunity to do a postdoctoral fellowship at Albert Einstein College of Medicine, where I am now. At Einstein, I have developed a robust computational pipeline for high-resolution morphology-accurate biophysical simulation of auditory neurons in the barn owl sound-localization system.