This project explores the strategic expansion and operational optimization of electric vehicle (EV) charging infrastructure within off-street parking systems under smart, sustainable mobility policies, using Taoyuan City as a case study. Participants will engage in applied research combining optimization modelling, data analysis, and scenario-based simulation to evaluate infrastructure investment decisions under regulatory and demand uncertainty. Research activities include analyzing EV and parking demand data, assisting in the development of optimization models (Python-based), conducting simulation experiments, and preparing a final report and presentation. Applicants should be undergraduate or graduate students in Industrial Engineering, Operations Research, Data Science, or related fields, with basic programming knowledge (Python preferred) and sufficient English proficiency for academic communication. Participants are expected to engage in research tasks actively, attend regular progress meetings, and complete a final presentation and report. The program emphasizes hands-on learning, interdisciplinary collaboration, and practical problem-solving in sustainable transportation systems.