AI-Based Faculty Performance Prediction System

Author(s)	Ms. Meena V, Mr. Purushothaman S, Mr. Sanjay S, Mr. Vasanth V
Country	India
Abstract	Faculty performance evaluation is important in higher education institutions to maintain academic quality and support professional development. Traditional evaluation methods are mostly manual, time-consuming, and may be biased. This project proposes an AI-Based Faculty Performance Prediction System that evaluates faculty performance using key parameters such as FDP programs attended, industrial visits conducted, courses handled, and research paper publications. The system provides separate role-based access for Admin, HOD, and Faculty to ensure secure data handling and effective monitoring. Machine learning techniques are used to predict faculty performance scores and generate useful insights. The proposed system improves transparency, reduces manual effort, and supports data-driven decision-making in academic institutions.
Keywords	Faculty Evaluation System-Decision Support System-Academic Performance Analysis- Automated Performance Monitoring-Secure Data Storage-Promotion Recommendation System.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 17, Issue 1, January-March 2026
Published On	2026-02-20

About IJSAT Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us	Message on WhatsApp	+91-9687-182-185	editor@ijsat.org

International Journal on Science and Technology