AI-ENABLED REVIEW MANAGEMENT SYSTEM AN INTEGRATED PLATFORM FOR AI-ASSISTED ACADEMIC SUBMISSION REVIEW

Authors

  • K. Harshwardhan Author
  • M. Navya Vani Author
  • Yaswanth Varma Author
  • N. Veneela Author
  • K. Karthik Author
  • Dr. Uttam Mande Author

DOI:

https://doi.org/10.62643/ijesat.v22i2(1).2493

Keywords:

Review Management; Artificial Intelligence; Node.js; Express.js; MongoDB; JWT Authentication; Gemini API; Role-Based Access Control

Abstract

The proliferation of digital academic and conference events demands scalable, consistent, and transparent submission review processes. This paper presents an AI-Enabled Review Management System (AI-RMS) built upon a Node.js/Express.js REST API backend with MongoDB persistence, integrating a Gemini-powered AI review engine to generate structured feedback for student submissions. The system supports three distinct roles—Administrator, Reviewer, and Student—governed by JWT-based authentication and role middleware. A quantitative reviewer rating model combining accuracy (60%), timeliness (30%), and workload (10%) enables rating-based workload distribution. Experimental deployment demonstrates reduced manual review latency, improved feedback consistency, and actionable reviewer performance analytics

Downloads

Published

07-04-2026

Issue

Vol. 22 No. 2(1) (2026): Volume 22, Issue 2(1), 2026

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

AI-ENABLED REVIEW MANAGEMENT SYSTEM AN INTEGRATED PLATFORM FOR AI-ASSISTED ACADEMIC SUBMISSION REVIEW. (2026). International Journal of Engineering Research and Science & Technology, 22(2(1), 100-104. https://doi.org/10.62643/ijesat.v22i2(1).2493