Volume 2 - Issue 2, March - April 2026

This study presents the development of RESEARCH-AID: Research Automation and Intelligent Documentation System, a hybrid AIpowered platform designed to streamline academic research management through automated capstone title generation and intelligent archiving. The system addresses common institutional challenges such as repetitive research proposals, inconsistent documentation, and inefficient title screening procedures. RESEARCH-AID employs a hybrid mechanism combining Natural Language Processing (NLP) for keyword extraction, machine learning clustering for topic categorization, and LLM-assisted generative modeling for producing unique and contextually aligned capstone titles. The archiving module integrates automated metadata tagging and similarity detection to prevent duplicate studies and improveaccessibility. Evaluation involving 40 undergraduate IT students yielded a usability score of 86.4 (Excellent) and a title-generation relevance accuracy of 91.7%. Results demonstrate that RESEARCH-AID significantly enhances research management efficiency, reduces redundancy, and supports academic innovation within higher education institutions.

Reginald S. Prudente, Jhon Denver Aloot, Rovic Clyde Germudo,"Enhancing Academic Research Management Through Automated Capstone Title Generation and Archiving System" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1605-1621) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.