In December 2025, Usha Shrestha enhanced the data preprocessing pipeline for image classification in the ABrain-One/nn-dataset repository. She implemented new data transformations and statistical computations tailored for 256-dimensional inputs, aiming to improve model accuracy and robustness. Using Python and PyTorch, Usha expanded the augmentation capabilities to support more complex input data, which enables more reliable and reproducible model training. Her work included clear commit documentation to ensure traceability of changes. While the scope was focused on a single feature, the depth of engineering addressed both technical and reproducibility challenges in machine learning data preprocessing and image processing workflows.