Christina Burge focused on enhancing test coverage and reliability for quantization features in the pytorch/pytorch repository, specifically targeting MobileNet V2 and V3 models on ARM64 architecture. She restored and re-enabled previously skipped quantization tests, addressing gaps in quality assurance for mobile model deployment. Using Python and leveraging her expertise in machine learning and unit testing, Christina validated the quantization test suite to ensure consistent pass rates and improved CI stability. Her work addressed a longstanding issue in PyTorch, deepening the robustness of quantization workflows for ARM64. The contributions reflect a targeted, quality-driven approach to software development.