Advancing previous research introduging DDPG and TD3 based safety value functions, to ensure robustness and safety in RL-based policies for quadruped robots.
Research Intern - Reinforced Learning
University of Trento
Designed and implemented PPO-based Walk and Stop policies for a quadruped robot. Conducted training in Nvidia IsaacSim + IsaacLab for Sim2Real on Unitree’s AlienGo.
Research Intern - Master Thesis
TXT E-TECH
Force-Driven validation system for cobots in autonomous aircraft testing, integrating Explainable AI (XAI) to enhance model interpretability. Migrated the system framework from ROS1 to ROS2, implementing hybrid CNNs with Grad-CAM for supervised deep learning. Achieved a classification F1-score of 96%-99.2%.
Student Researcher
Politecnico di Milano
Design and Control of an actuated rig to simulate wind disturbances and collision events for drone stability testing. Sensor fusion: IMUs, gyroscopes, and Hall effect sensors.
Co-Founder & Arbitrator (Former Head of Projects, Vice & President)
Automation Engineering Association (AEA)
Co-founded the Automation Engineering Association (AEA) at Politecnico di Milano, driving student involvement in robotics and automation. Served in leadership roles, including Head of Projects (2021), Vice President (2022), and President (2022-2023), before transitioning to the Arbitrator role. Led national expansion efforts, supervised over 110 students in research projects, and organized technical workshops and industry collaborations.
Education
PhD. Robotics
Technology University of Eindhoven & BMW AI Robotics
Topic: Robust multimodal perception and learning in robotics and intelligent vehicles.
Research focuses on multimodal perception and learning for robots, emphasizing object manipulation, environment interaction, and adaptive behaviors. Parallel work involves human-vehicle interaction.
MSc. Automation and Control Engineering
Politecnico di Milano
GPA 3.78/4.0. Main courses: Advanced Control, Robotics, Machine Learning, IoT, Autonomous Vehicles and Power Electronics.
BSc. Automation Engineering
Politecnico di Milano
GPA 3.41/4.0. Gained strong fundamentals in control, robotics, embedded systems, industrial automation, sensor technology, and signal processing.