Shima's research focuses on developing an AI-driven flash flood alert system to rapidly detect and notify residents of flash flood events in New York City. Additionally, machine learning models are being utilized to predict real-time flood depth with high accuracy. The proposed system is intended to enhance urban risk management and disaster preparedness while serving as a scalable solution for flood-prone metropolitan areas.