Alexis Yslau enhanced data quality and processing pipelines for the roman-corgi/corgidrp and spacetelescope/catkit2 repositories, focusing on robust support for large astronomical datasets. Using Python, C++, and NumPy, Alexis implemented 64-bit data handling, improved nonlinear pixel flagging, and introduced decimal-to-binary flag mapping to streamline data validation and interoperability. The work included refining metadata formatting, enforcing endianness, and aligning file naming conventions to ensure reproducibility. Alexis also strengthened code quality by addressing linting, documentation, and DCO compliance, while maintaining and extending automated testing with Pytest. The depth of these contributions improved maintainability and reliability across both codebases.