As an applied mathematician specializing in data-driven analysis, I bring expertise in model- and data-order reduction (Koopman/Dynamic Mode Decomposition, Proper Orthogonal Decomposition, etc.), time-series analysis, and statistical learning. I have developed a custom Dynamic Mode Decomposition (DMD) framework—an unsupervised learning approach—for extracting coherent structures and temporal dynamics from aerospace, oceanographic, and environmental datasets. I further extended this framework for real-time detection by integrating regression-based predictive models.