Contributed to the KU-BIG repositories by building and documenting a suite of natural language processing and deep learning assets, including Jupyter notebooks for text preprocessing, word embeddings, sentiment analysis, and sequence models. Established foundational project scaffolding and enhanced onboarding through clear documentation of modeling capabilities and asset management. Expanded the KU-BIG/KUBIG_2025_SPRING repository with hands-on experimentation resources, such as BERT-based news classification, transformer-based chatbots, and parameter-efficient fine-tuning tutorials. Leveraged Python, PyTorch, and Hugging Face Transformers to accelerate reproducibility and exploration cycles, while maintaining a focus on project maintainability, knowledge sharing, and readiness for upcoming NLP contests and features.