Inspiration
We noticed that student housing is often inflexible and mismatched. Many students end up overpaying for leases, struggling to find compatible roommates, and relocating frequently for internships or jobs. We wanted to build something that gives students more flexibility and helps them find people they actually enjoy living with.
What it does
Scholar House is a roommate-matching and housing platform for students. It helps users find housing and roommates based on shared interests, lifestyle, dietary preferences, and budgets showing a personalized compatibility score for each match.
How we built it
We built the backend using Java (Spring Boot) and PostgreSQL for data storage, and the frontend with React + TypeScript. Our matching engine uses weighted scoring to calculate compatibility percentages between users.
Challenges we ran into
Integrating multiple microservices and aligning real-time data across them was challenging. Designing a meaningful matching algorithm and ensuring smooth communication between frontend and backend also took iteration and testing.
Accomplishments that we're proud of
We’re proud that we turned a real student problem into a functional prototype. Our matching system accurately reflects lifestyle compatibility, and the UI makes it easy for students to explore potential roommates.
What we learned
We learned how to build scalable microservices, integrate a matching algorithm into an existing system, and collaborate effectively under time pressure. We also gained insight into real-world user needs in student housing.
What's next for Scholar House
We plan to integrate Scholar House into our larger Studentbnb ecosystem, add AI-driven roommate recommendations, enable flexible lease listings, and support verified student communities across universities.
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