AI Hackathon Applicant Ranker

Summary

Developed a backend application that ranks applicants for a hackathon based on their skills and experience. Built scoring logic that assigns weighted points for demographic diversity, academic excellence, and underrepresented backgrounds. Integrated Google Gemini API for intelligent essay evaluation with sentiment analysis. Designed database schema and queries to efficiently retrieve and process applicant information from Supabase. Backtested on previous hackathon application data to ensure accuracy and optimal rankings.

Feature List

• Multi-criteria Scoring Algorithm: Evaluates applicants across 8+ weighted factors including school prestige, graduation year, major diversity, and first-time hacker status
• AI-Powered Essay Analysis: Leverages Google Gemini AI to assess applicant motivation and interest through natural language processing, scoring responses on passion and project-specific interest
• Database Integration: Connects to PostgreSQL database to process applicant data and return ranked results
• Scalable Architecture: Modular design allows for easy adjustment of scoring weights and criteria based on organizational needs