Mikaela Angel reimplemented the Marching Cubes algorithm in the NVIDIA/warp repository, migrating the codebase from C++ to pure Python using Warp. This transition enhanced cross-platform compatibility and enabled differentiability, allowing the algorithm to be integrated more flexibly into Python-based research and machine learning pipelines. By preserving API parity and reducing build complexity, Mikaela streamlined the development workflow and improved accessibility for both researchers and engineers. The work leveraged skills in algorithm implementation, geometry processing, and GPU computing, resulting in a robust solution that maintained feature parity while enabling tighter integration with the Warp runtime and supporting modern experimentation needs.