M.Sc. Student in Artificial Intelligence Systems @ UniTN | Robotics & Automation Path
I am an AI Engineer specializing in Robotics. My work focuses on developing autonomous systems that perceive, reason, and interact with the physical world through advanced control theory and parameter-efficient deep learning.
| Domain | Tools & Technologies |
|---|---|
| Robotics & Control | ROS, URDF, Kinematic & Dynamic Modeling, Task-Space Control |
| Artificial Intelligence | PyTorch, Transformers, LLM Adaptation (LoRA), RAG |
| Computer Vision | OpenCV, Object Detection, Feature Extraction, Vision-Language Models |
| Software & DevOps | Python (Expert), C++, Git, Docker, SQL (PostgreSQL) |
Focus: Robotics, Automation, Kinematics
- Designed and implemented a task-space control architecture for a UR5 industrial arm.
- Solved redundancy and singularity issues using Differential Kinematics and Jacobian matrix optimization.
- Developed the system in Python, utilizing URDF for robot modeling and ROS for simulation and control.
Focus: Deep Learning, Multi-modal AI, Computer Vision
- Developed a hybrid system to adapt Vision-Language Models (CLIP) for semantic scene understanding.
- Implemented LoRA (Low-Rank Adaptation) to enable few-shot learning on robotic vision tasks without full retraining.
- Integrated Tip-Adapter-F architectures to balance zero-shot capabilities with specialized class recognition.
Focus: NLP, LLM, Interaction
- Fine-tuned BERT for joint Intent Classification and Slot Filling, crucial for Human-Robot Interaction (HRI).
- Optimized inference pipelines achieving 97.8% Accuracy, ensuring real-time responsiveness for verbal command processing.
Focus: SQL, Docker, System Architecture
- Engineered a scalable database architecture using PostgreSQL for complex data relation management.
- Containerized the entire stack via Docker, ensuring deterministic deployments and environmental parity.
- Implemented secure API layers with Node.js and JWT authentication.
- Industrial AI Internship @ Fondazione Bruno Kessler (FBK): Developed predictive maintenance pipelines in Python (Pandas/NumPy) for vibrational signal analysis in automated industrial systems.
- Academic Path: Currently attending M.Sc. in AI Systems (100% English taught). Core coursework includes Machine Learning (12 CFU), Deep Learning, and AI applied to Robotics.
