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Yalie Search

AI-powered student directory with multimodal search — combining CLIP, semantic text, and GPT-powered query expansion across 6,000+ Yale students with 2-3x retrieval accuracy.

Machine Learning Python Next.js CLIP FastAPI

Overview

Yalie Search is an AI-powered student directory enabling natural language queries across 6,000+ Yale students by interests, skills, and appearance — achieving 2-3x retrieval accuracy vs. keyword search through GPT-powered query expansion.

Architecture

Multimodal search architecture combining three complementary systems:

  • CLIP Vision Embeddings — Profile images encoded with CLIP ViT-Large-Patch14 for visual similarity
  • Semantic Text Search — Natural language understanding for interest and skill-based queries
  • Structured Metadata Matching — Filters for residential college, graduation year, and major
  • GPT-Powered Query Expansion — Intelligent reformulation for broader, more accurate results

Automated profile generation for 3,600+ students with privacy-first design.

Tech Stack

Backend: FastAPI, PyTorch with CLIP, OpenAI API, Yale CAS (OAuth authentication)

Frontend: Next.js 14, TypeScript, Tailwind CSS, Framer Motion

Infrastructure: Railway (Docker), Vercel — sub-5s search response times

Key Features

  • Natural Language Search — Find people using descriptive queries
  • Advanced Filters — Filter by residential college, graduation year, and major
  • Find Similar — Click any result to discover visually similar people
  • Gamified Engagement — Leaderboards for trending searches and most-viewed profiles
  • Anonymous Mode — Search privately without logging to history
  • Content Moderation — AI-powered filtering using GPT-4o-mini