Biography
I am a Mathematician and Research Scientist with a Ph.D. in Applied Mathematics and a graduate minor in Computer Science from Louisiana State University. My research lies at the intersection of mathematics, dynamical systems, and machine learning, with a focus on applying mathematical theory to modern data-driven challenges.
My current work explores the Koopman operator framework for analyzing nonlinear dynamical systems, developing data-driven techniques to approximate Koopman semigroups. I also study higher-order neural networks and topological deep learning, aiming to integrate abstract mathematical structures with state-of-the-art machine learning methods.
Driven by both theoretical insight and real-world application, my goal is to contribute foundational tools that advance our understanding of complex systems in science, engineering, and artificial intelligence.