Hayden Ringer is a PhD student in applied and computational mathematics at Virginia Tech with eight years of experience building numerical software and statistical models. His research combines numerical linear algebra, optimization, and vector calculus to produce practical tools—most notably a dairy cattle diet optimization framework and a competitive Python package for multivariable root-finding. He has applied Bayesian methods to real-world problems from historical earthquake reconstruction to social determinants of health and has implemented fast numerical methods at national labs. Hayden teaches numerical methods and data science, bringing classroom pedagogy into reproducible software and research workflows. He is comfortable turning mathematical theory into production-capable code and is exploring statistical questions about eigenvalues inspired by “hearing the shape of a drum.”
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Mathematics, Doctor of Philosophy - PhD, Mathematics at Virginia Tech
Master of Science - MS, Mathematics, Master of Science - MS, Mathematics at Brigham Young University
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