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LucaFilippetti99/README.md

Luca Filippetti 👋

Computer Engineer | AR/VR Specialist
🌐LinkedIn | 📄CV | ✉️ filippetti99.lf@gmail.com | 📍 Turin, Italy

ARBoard Research Fellow @ ARBoard (Politecnico di Torino)

  • Project: AR for PCB debugging on smart glasses (Unity, C#, AR Foundation, OpenCV, ML).
  • Award: University Fair Award - Best Demo @ DATE 2025 Conference.
  • Recognition: Selected for the PoC Launchpad by Fondazione Compagnia di San Paolo.
  • Publication: 2025 IEEE International Symposium on Emerging Metaverse (ISEMV): document.

🛠️ Skills

  • AR/VR: Unity, Blender
  • Dev: C#, Python, OpenCV, Machine Learning, Git
  • Other: Computer Vision, Image Processing, Software Engineering

MSc Computer Engineering (Graphics & Multimedia) @ Politecnico di Torino.

Pinned Loading

  1. GymTonic GymTonic Public

    Demo project for HCI course - Politecnico di Torino. Fitness/workout application prototype.

    JavaScript

  2. Study-Hall-Seat-Detection-System Study-Hall-Seat-Detection-System Public

    A Computer Vision project developed at Politecnico di Torino to monitor seat occupancy in study halls. It utilizes YOLOv4 for person detection and a custom temporal consistency algorithm to classif…

    Python

  3. EzWh---Software-engineering-project EzWh---Software-engineering-project Public

    EZ Warehouse is a comprehensive warehouse management system developed for the Software Engineering course (MSc Computer Engineering @ Politecnico di Torino).

    JavaScript

  4. PromptDoctor PromptDoctor Public

    PromptDoctor: A Vibe-Coded, Gamified Prompt Engineering Tool. Powered by Local AI (Ollama), LangGraph Multi-Agent Reasoning, and real-time Streamlit UI streaming.

    Python

  5. Robotic-programming-by-imitation_haptic-devices-and-machine-learning-to-recognize-user-actions. Robotic-programming-by-imitation_haptic-devices-and-machine-learning-to-recognize-user-actions. Public

    Forked from AlbertoSabater/Domain-and-View-point-Agnostic-Hand-Action-Recognition

    MSc Thesis Politecnico di Torino: Robot control via MANUS hand action recognition. Custom 5k+ frame dataset. Pipeline: Pose → ML → Robot → Unity WebRTC.

    Python