Campus Career Hub: A MERN Stack Based Placement Portal

Abstract

The Campus Career Hub is a MERN stack-based digital platform designed to revolutionize the campus recruitment process by providing a centralized, secure, and scalable system. It offers features like job posting, student application tracking, and JWT authenticated user access. . The platform integrates job postings, applications, and aptitude assessments into a single, user-friendly interface. Leveraging the MERN stack’s flexibility and performance, the web application ensures scalability across platforms while maintaining a consistent and responsive user experience. This document outlines the system’s architecture, key features, and its role in enhancing campus recruitment process. This paper presents the system\'s architecture, design methodology, implementation, and evaluation based on testing and user feedback, highlighting its effectiveness in reducing manual efforts and enhancing placement outcomes.

Introduction

Campus Career Hub is a modern, integrated web application designed to streamline and enhance the campus placement process. Built using the MERN stack (MongoDB, Express.js, React.js, Node.js), it offers a scalable, interactive, and user-friendly platform that automates key recruitment workflows and facilitates communication between students, recruiters, and administrators.

The system features role-based access control, allowing students to browse and apply for jobs, take aptitude tests, upload resumes, and track applications in real time. Recruiters can post jobs, filter applicants, and review candidate profiles, while administrators oversee overall system activity and user management. The centralized dashboard consolidates assessments, application tracking, and communication tools, promoting transparency, efficiency, and seamless user experience across devices.

The backend uses Node.js and Express.js for server logic and routing, MongoDB for data storage including resumes via GridFS, and JWT for secure authentication. The React.js frontend ensures a dynamic and responsive interface. The modular architecture supports scalability and maintainability, with strong emphasis on security and data validation.

Testing with users showed high satisfaction (95%) compared to traditional methods, successful resume uploads, and effective recruiter access to candidate data. Integration tests confirmed stable, secure performance. The system thus offers a robust, efficient, and accessible solution for modern campus recruitment challenges.

Conclusion

Campus Career Hub effectively addresses the limitations of conventional placement systems. It enhances user engagement, transparency, and operational efficiency. Future upgrades include mobile application development, interview scheduling, and AI-based candidate-job matching. Moreover, the platform\'s responsive design and robust architecture ensure seamless performance across devices and scalability for deployment in institutions of various sizes. The integration of features like real-time application tracking, eligibility filtering, and secure authentication contributes to a transparent and efficient placement process. These elements collectively reduce the administrative burden while empowering students to take greater control of their career journey. Looking ahead, future enhancements aim to further increase the system\'s utility and adaptability. Planned upgrades include the development of a dedicated mobile application to improve accessibility on-the-go, automated interview scheduling to streamline communication between candidates and recruiters, and AI-driven candidate-job matching to improve the accuracy of application filtering. With these enhancements, Campus Career Hub is poised to evolve into a more intelligent and comprehensive platform, capable of meeting the growing demands of modern campus recruitment.

References

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Copyright

Copyright © 2025 Savita Mogare, Varesh Wani, Kunal Suryawanshi, Nishant Vaifal, Laukik Ghude. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.