Aravikumar contributed a targeted robustness improvement to the nvidia-holoscan/holohub repository, focusing on the EndoNeRF data ingestion pipeline. Using Python and leveraging skills in data processing and error handling, Aravikumar addressed a loader bug that caused frame misalignment across images, depths, and masks. The solution involved aligning all data sources to the minimum available frame count, introducing truncation logic, and implementing clear warnings and error messages when inconsistencies occurred. This work stabilized data loading for surgical_scene_recon datasets, reducing runtime failures and improving reliability for model training and evaluation. The fix demonstrated careful debugging and thoughtful data validation practices.