During October 2024, contributed to the IBM/data-prep-kit repository by developing semantic profiling and concept extraction capabilities for the code profiler. This work involved implementing higher-order syntactic profiling and integrating report generation based on extracted Universal Abstract Syntax Trees (UAST) and identified concepts. Leveraging Python for code analysis and data transformation, the solution expanded profiling insights across multiple libraries and languages, supporting deeper code understanding and data-driven optimization. The feature was validated end-to-end within the repository, resulting in improved profiling accuracy and enhanced readiness for reporting. No bugs were recorded during this period, reflecting a focused and robust feature delivery.