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Building FacultyFinder.io: An AI-Powered Academic Discovery Platform with Smart CV Matching
Demoing an AI platform matching researcher CVs to Canadian faculty using web scraping, multi-LLM analysis, and PostgreSQL semantic search on 42k+ publications.
FacultyFinder.io is a comprehensive platform that helps researchers discover and connect with faculty members across Canadian universities using AI-powered matching and intelligent web scraping. I’ll demo the complete technical pipeline:
- Comprehensive Data Source: Combining different sources of data (names from the university website, publications from PubMed, and OpenAlex)
- AI-Powered Profile Analysis: Multi-LLM CV analyzer (Claude, GPT, Gemini, Grok) that extracts research interests, keywords, and skills from uploaded CVs/resumes
- Smart Matching Engine: Database-driven faculty recommendation system using PostgreSQL with semantic matching
- Publication Integration: OpenAlex API integration with ORCID-based disambiguation, processing 42,595+ publications with 88.6% file size optimization
- Real-time RESTful API: FastAPI backend serving 10+ endpoints with advanced filtering and search
The demo will show: uploading a CV, the AI extracting research keywords, querying our database of 500+ faculty members, and generating personalized recommendations with match scoring. I’ll walk through the code for the web scraper, the CV analysis prompt engineering, and the database schema optimization.
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