During February 2025, Seokhwan Yoon focused on enhancing the correctness and robustness of batched matrix-vector operations in the JuliaGPU/CUDA.jl repository. He addressed a bug affecting batched GEMV computations, particularly for transposed matrices and varying batching scenarios, by introducing dimension consistency checks and comprehensive tests. His work leveraged Julia and CUDA, applying expertise in GPU computing and linear algebra to ensure reliable handling of edge cases. By improving input validation and expanding test coverage, Seokhwan reduced the risk of dimensionality errors and user-facing failures. The depth of his contribution reflects careful attention to both algorithmic correctness and practical reliability.