In April 2025, Dan enhanced the pixel sampling pipeline for nerfstudio by refactoring its logic to efficiently handle variable-resolution image batches. Using Python and leveraging batch processing and data processing skills, Dan introduced a defaultdict-based approach for robust storage and collation of sampled pixel data. This ensured that both images and depth images were correctly sampled and organized, regardless of input resolution diversity. The work improved the reliability, scalability, and performance of the batch processing pipeline within the nerfstudio repository. Dan’s contribution addressed the challenge of maintaining data integrity across heterogeneous datasets, laying a foundation for future scalable computer vision workflows.