I am a postdoctoral researcher at the Industrial Robotics Facility (INBOT) of the Italian Institute of Technology (IIT), where I develop control methods for complex robotic systems. My current work focuses on tendon-driven continuum robots for the manipulation of soft and deformable objects.
My main research interest is the development of hybrid robotic control architectures that combine classical and model-based control with reinforcement learning. The goal is to retain the structure, interpretability and reliability of established control methods while using learning to improve adaptability and robustness against modelling errors, nonlinear dynamics and changing operating conditions.
I hold a PhD in Robotics and Intelligent Machines (DRIM), completed within the Italian doctoral programme of national interest coordinated by the University of Genoa, with my research activities carried out at Università Politecnica delle Marche. I previously earned a Master’s degree in Mechanical Engineering from Università Politecnica delle Marche and a Bachelor’s degree in Industrial Engineering from the University of Trento.
During my PhD, I worked across robot learning, human–robot interaction, robotic perception and industrial automation. My research included reinforcement-learning-augmented operational-space control, learning from demonstration, markerless motion capture and gesture imitation for rehabilitation robotics, as well as collaborative assembly, robotic surface finishing and safety evaluation. These activities involved applied research at i-Labs Industry and collaborations with VTT Technical Research Centre of Finland on learning-based industrial robotics and CNR-ISTC on robotic perception and rehabilitation. Before beginning my doctoral research, I worked as a reliability engineer at Tecram, strengthening my background in system analysis, risk assessment and engineering decision-making.
My background spans mechanics, mechatronic design, electronics, sensing, software, computer vision, artificial intelligence and control. This gives me a systems-engineering perspective: I approach a robot as a complete integrated system and can work across the full development chain, from mechanical design and prototyping to perception, control, ROS integration and experimental validation.
My broader goal is to combine rigorous engineering with learning-based adaptation to develop robotic systems that remain reliable and effective outside controlled laboratory conditions.
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