Andrew Wang developed and integrated a cosine similarity evaluation metric into the deepinv repository to enhance image reconstruction benchmarking. Using Python and leveraging data analysis and machine learning skills, he implemented the metric to compare reconstructed images against ground truth, ensuring accurate assessment of reconstruction quality. The approach included correct metric inversion and configuration to align with evaluation semantics, along with comprehensive updates to tests, documentation, and the changelog for CI compatibility. Andrew’s work improved the clarity and maintainability of metric evaluation within deepinv, providing clearer signals for model performance and supporting robust, reproducible benchmarking in the library’s workflow.