Devang worked on the pytorch/ao repository, where he developed ArmInductorQuantizer support for Pt2e quantization on ARM architectures. His work focused on enabling quantization for conv2d and linear layers, with comprehensive unit tests to ensure correctness and reliability. Using Python and leveraging PyTorch’s quantization and machine learning capabilities, Devang addressed CI reliability by improving style adherence and fixing validation workflows. He expanded test coverage for various quantization scenarios, laying the groundwork for broader ARM hardware deployment. The depth of his contribution is reflected in the integration of new quantization features and the attention to robust, automated testing and code quality.