University
Shawnee State University
Major
Computer Engineering Technology
Student Type
Undergraduate Student
Presentation Types
Poster Presentation (Live)
Abstract
Merge addresses a significant gap in the online dating market by creating a specialized platform for career-driven professionals. Traditional dating apps often fail to meet the needs of ambitious individuals seeking partners who understand their professional commitments and share similar career values. This project implements a web-based MVP that integrates LinkedIn authentication to verify professional credentials and import career data, creating an environment where professional compatibility becomes a primary matching criterion. The system architecture employs React.js for the frontend, Node.js with Express for the backend, and MongoDB for data storage, enabling rapid development and future scalability. Key innovations include a professional profile system that maintains appropriate separation between professional identity and dating preferences, and a specialized matching algorithm that prioritizes career alignment. This solution transforms relationship-building for ambitious professionals by connecting individuals with compatible career trajectories and professional values.
Human and Animal Subjects
no
IRB or IACUC Approval
yes
Faculty Mentor Name
Jeong Ok
Faculty Mentor Title
Assistant Professor
Recommended Citation
Wilson, Jevin, "Merge: The Dating Platform for Career Professionals" (2025). Celebration of Scholarship. 7.
https://digitalcommons.shawnee.edu/cos/2025/posters/7
Location
Morris UC Lobby
Merge: The Dating Platform for Career Professionals
Morris UC Lobby
Merge addresses a significant gap in the online dating market by creating a specialized platform for career-driven professionals. Traditional dating apps often fail to meet the needs of ambitious individuals seeking partners who understand their professional commitments and share similar career values. This project implements a web-based MVP that integrates LinkedIn authentication to verify professional credentials and import career data, creating an environment where professional compatibility becomes a primary matching criterion. The system architecture employs React.js for the frontend, Node.js with Express for the backend, and MongoDB for data storage, enabling rapid development and future scalability. Key innovations include a professional profile system that maintains appropriate separation between professional identity and dating preferences, and a specialized matching algorithm that prioritizes career alignment. This solution transforms relationship-building for ambitious professionals by connecting individuals with compatible career trajectories and professional values.
