Nathan Speck received his B.S. in Mathematical Physics from University of Waterloo in 2017. He has been interested in image processing and machine learning techniques since then, and has focused his efforts on spectral imaging at KA Imaging for 3 years.

Jacqueline Alvarez is a Ph.D. candidate in the Applied Mathematics Department at the University of California, Merced. Her research interests are deep learning and machine learning for image processing applications. Jacqueline has participated in multiple summer programs at Lawrence Livermore National Laboratory (LLNL), including the Data Science Challenge, Data Science Summer Institute, and Computing Scholar Program. The work she is presenting is a result of her collaboration with LLNL.

Dr. Michelle Espy is a scientist in the Non-Destructive Testing Group at Los Alamos National Laboratory. Her specific areas of interest include novel nuclear magnetic resonance techniques for detection of illicit materials, methods of imaging based on x-ray, neutron, and proton radiography, and computed tomography for characterization of materials. In 2014, Michelle was made a Fellow of the American Physical Society in the Division of Nuclear Physics. In 2023 she attained her ASNT Level III in radiography. Michelle has over 90 peer reviewed publications and 6 patents. But her proudest professional accomplishment is mentoring dozens of students and post-docs.