Worked on the pytorch/pytorch and pytorch/rl repositories, focusing on improving error handling and data manipulation in Python and PyTorch environments. Enhanced error messaging for argument exceptions by refactoring multiple modules to deliver clear, consistent feedback, which improved debugging efficiency and user experience. In the pytorch/rl repository, developed new methods for the ReplayBuffer to support in-place value setting and updates, increasing flexibility for reinforcement learning workflows. Addressed a bug in the MultiOneHot class to ensure correct numpy array outputs, accompanied by expanded unit testing. Demonstrated strengths in debugging, data structures, and object-oriented programming to support robust, maintainable code.