Experience

  1. Research Collaborator - Reinforced Learning

    University of Trento
    Advancing previous research introduging DDPG and TD3 based safety value functions, to ensure robustness and safety in RL-based policies for quadruped robots.
  2. 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.
  3. 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%.
  4. 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.
  5. 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

  1. 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.
  2. 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.
  3. 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.
Skills & Hobbies
Technical Skills
Python
C++
ROS
Hobbies
Powerlifting
Drummer
Enduro and Downhill
Languages
100%
Italian
85%
English
70%
Spanish
10%
German