Shewu worked on the pytorch/executorch repository, focusing on stabilizing quantized inference for 16-bit LayerNorm operations. Addressing a critical bug, Shewu corrected the quantization annotation logic and implemented comprehensive unit tests to ensure ongoing reliability, particularly for the 16a4w LayerNorm configuration. This work involved close alignment with Qualcomm AI Engine Direct integration, ensuring compatibility with external toolchains and deployment environments. Using Python and leveraging expertise in machine learning and quantization, Shewu’s contributions improved the robustness and deployment readiness of quantized models. The depth of the work is reflected in the preventative testing and careful integration with broader system requirements.