Addison CB

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Anigraph

Full-stack anime discovery platform leveraging Neo4j graph database to explore connections across 22,000+ titles through 380,000 staff, studio, genre and tag relationships with real-time filtering and interactive visualizations.

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Key Features:

→ Engineered complete ETL pipeline with parallelized web scraping, Python-based data transformation scripts, and bulk loading into Neo4j and Elasticsearch
→ Architected microservices stack with Docker Compose orchestrating Nginx reverse proxy, Nuxt.js SSR, Neo4j graph database, Elasticsearch, and Umami analytics
→ Built interactive D3.js force-directed graph visualization showing anime staff connections with role-based edge weights and dynamic node layouts
→ Implemented hybrid client-server filtering system with preloaded metadata achieving instant filter count updates and multi-dimensional search across studios, genres, tags, and eras
→ Developed comprehensive staff and studio pages with filmography categorization (11 role types), collaboration timelines, production mappings, and genre/tag analytics
→ Deployed containerized production stack with automated SSL certificate renewal and resource-optimized configuration across 5 services

Nuxt.js 3 Vue 3 TypeScript Neo4j Elasticsearch D3.js Docker Vuetify

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Facial Recognition Graph Search

RGBAttack, or "Relationship Graph Based Attack", is an open-source intelligence (OSINT) tool designed to help users discover information about individuals captured in photos.

Key Achievements:

→ Built a Python backend with RESTful APIs for image upload, facial detection (OpenCV), and structured graph data generation
→ Engineered an interactive frontend using JavaScript and vis.js for real-time graph rendering, node editing, and depth-based visual scaling
→ Implemented Excel (.xlsx) export via API endpoints for offline graph and metadata analysis
→ Designed the system for scalability and responsiveness with asynchronous pipelines and caching strategies