Gassan Salama focused on resolving a critical bug in the uxlfoundation/oneDNN repository, addressing incorrect padding and iteration logic in the AArch64 JIT backward weights path for convolution and depthwise kernels. By refining the padding calculations to account for output height and stride, and incorporating top padding stride for 256-wide backward weights kernels, Gassan improved the correctness and reliability of kernel parameter computation. Working primarily in C++ and leveraging expertise in CPU optimization and low-level programming, Gassan’s targeted fix enhanced ARM performance and reduced the risk of processing errors, enabling safer production deployment on embedded ARM architectures.