Urban development and investment are often uneven, which can leave certain neighborhoods overlooked for decades while nearby neighborhoods grow quickly. My project breaks down how Ai could identify these underdeveloped urban areas to find opportunities for responsible real estate investment and community growth. At the same time, I will look at the human factors that explain why some areas remain untouched. I want to see if AI tools can analyze public data, such as property records, development history, and demographic trends, to highlight neighborhoods that have seen limited development over the last 25 years.

I am conducting this research in partnership with Rafyana Realty Corps under the guidance of Sam Shpilfogel, but I still will be in contact with his team. The project involves gathering human and real estate data and using AI to analyze patterns of development across different neighborhoods. My models will look at factors like construction activity, property values, zoning changes, and infrastructure investment to identify potential development opportunities. I will be asking for advice from Sam and I will try to mimic their strategies using Ai to improve and help the strategies and patterns AI will use and build.

The goal of this project is to show how AI can be used as a tool for real estate professionals to help find overlooked areas more efficiently. By making it easier to discover investment opportunities. This AI assisted analysis could help lead to smarter urban planning and encourage growth in communities that have not yet benefited from recent economic trends.