Jeffrey Utley
Below is a selection of software packages and coding projects I have developed for research, coursework, and personal interest. You can find more on my GitHub profile.
An installable Python package implementing the ReVAR (Re-whitened Vector AutoRegression) algorithm for aero-optic modeling and synthetic phase-screen generation. Unlike traditional physics-based models, this fully automated, data-driven approach learns the spatial and temporal statistics of optical turbulence directly from data. Validated on two wind-tunnel datasets, it achieves a worst-case NRMSE of 4% for temporal power spectrum matching. Includes package installation scripts, thorough documentation, and reproducible examples.
An installable Python package for boiling-flow parameter estimation and anisotropic phase-screen generation. Used to generate statistically validated synthetic data on two wind-tunnel datasets (worst-case NRMSE = 12% for temporal power spectrum match). Includes package installation scripts and reproducible examples.
A Python package implementing the Mirror Descent algorithm with reproducible demos and install scripts. Demonstrates algorithm implementation, packaging discipline, and mathematical optimization techniques.
MATLAB implementation of the algorithm from my undergraduate research article in Involve. Used for computing conformal maps and analyzing complex analysis problems.