Research Assistant
CurrentEngaged in research for "Understanding Factors Influencing Electric Vehicle Adoption in Baltimore", using machine learning to analyze data for policy development and infrastructure planning.Developed algorithms to extract data from EV license plates, classify EV models, and analyze charging duration to understand usage patterns.Conducted data cleaning, feature engineering, and model training to support EV adoption strategies, creating insights to inform transportation planning.Utilized Python for data analysis and visualization, contributing to data-driven recommendations on EV infrastructure placement and usage trends.