Raman Y. Avarzaman

Developed a real-time human–computer interface that uses the parallax effect to create a 3D illusion on a 2D screen.

• Implemented face detection and tracking using Python with OpenCV and MediaPipe, enabling dynamic interaction based on user movement.
• Integrated face detection data with Godot and Unity projects for visualization via UDP networking.
• Conducted performance evaluations and user studies to assess effectiveness.
• Implemented Kalman filtering to smooth MediaPipe data.
• Documented experiments and results for reproducible guidance.

Developed and deployed an automated housing monitoring system for real-time listing alerts.

• Engineered a robust web scraping solution using Python's Scrapy library.
• Developed real-time notifications via WhatsApp (Green API) and Telegram bot.
• Deployed on VPS with automated scheduling using cron.
• Implemented proper logging and monitoring systems.

Collaborated on a Java-based routing engine to analyze socio-economic accessibility using GTFS data.

• Developed routing algorithm integrating GTFS public transport data with geographical datasets.
• Implemented distance and time calculator for postal codes using coordinates.
• Created visualization tool for transport routes.
• Optimized SQL queries and integrated bus routes into GUI.
• Utilized JUnit for testing with high code coverage.

Built and maintained a Proxmox-based home lab focused on self-hosting, media automation, and reliable infrastructure.

• Designed and operated a Proxmox-based home lab (Dell Optiplex 7050, Intel i5-7500).
• Configured Linux VMs and containers for media, automation, and services.
• Implemented Intel HD 630 iGPU acceleration for media workloads.
• Deployed Jellyfin media server with Sonarr v4 and Radarr integration.