Axel Fraud

Axel began working with Dr. Longland’s group as a freshman in 2022, originally focused on analyzing peaks in magnetic spectrograph data. Starting in Julia and later transitioning to Python, he is now developing a Bayesian framework using MCMC techniques to extract nuclear energy information through Gaussian and Voigt profile fitting. His work supports more precise and reliable analysis of reaction products.

Fun Fact: He has a wide range of sporty hobbies, but surfing is his all-time favorite way to stay active and recharge.