Julian Giesen developed scheduling enhancements and advanced visualization features for the CombiRWTH/StaffScheduling repository, focusing on improving planning accuracy and reporting. He implemented a Python-based command that enables concurrent solving of multiple scheduling cases, exporting results in a structured format to streamline downstream data processing. By extending the employee visualization to include hidden actual working time, Julian increased the fidelity of workforce analytics and data representation. His work strengthened the data processing pipeline, supporting new export and visualization capabilities. Leveraging skills in Python, algorithm design, and back end development, Julian delivered features with depth, addressing both scalability and data integrity.