Cole Thompson is a scientist and radiation transport specialist with nine years of experience applying computational modeling, machine learning, and data-driven methods to nuclear and radiation engineering problems. Based at Los Alamos National Laboratory, he develops radiation transport applications and advanced non-destructive assay techniques that have dramatically improved plutonium mass and multiplication estimates and classification accuracy for detector data. His work spans algorithm development for multi-channel neutron data, event-based imager analysis, and leveraging modern ML architectures—including Transformers and hybrid U-Nets—for challenging vision and signal tasks. Trained with a PhD in Nuclear Engineering and a multidisciplinary BS in Biochemistry and Astronomy from UT Austin, he bridges physics-driven simulation (MCNP) and cutting-edge data science. Notably, his research has turned detector geometry and pre-assay information into order-of-magnitude gains in predictive performance, underscoring a practical knack for turning domain knowledge into measurable improvements.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Nuclear Engineering, Doctor of Philosophy - PhD, Nuclear Engineering at The University of Texas at Austin
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