Our research spans medical robotics, industrial automation, innovation management, and sustainable education — always with human interaction at the centre.
An active project developing an RFID-based laparoscopic system for intraoperative detection of small colorectal tumors, targeting improved surgical precision in minimally invasive oncological procedures.
An Erasmus+ consortium project building a digital ecosystem and open educational resources to embed sustainable development competencies across European higher education curricula.
Developed a VR-enhanced robotic exoskeleton for upper-limb cardiac rehabilitation, combining immersive visual feedback with motorised assistance to support post-infarction motor recovery.
Designed an expert system enabling industrial robots to perform adaptive, knowledge-driven tasks in dynamic manufacturing environments, advancing intelligent automation capabilities.
Developed an integrated software platform modelling and optimising the product-service lifecycle for SMEs, supporting the transition from product-centric to servitisation-based business models.
Research into novel robotic perimeter security systems designed for rapid on-site assembly and modular reconfiguration in industrial and critical infrastructure settings.
Investigates non-invasive intraoperative detection of small endoluminal digestive tumors using magnetic and proximity sensor arrays, focusing on precise margin delineation during minimally invasive surgery.
Optimised the control algorithm of the CardioVR-ReTone exoskeleton by integrating EMG and heart-rate sensors with a supervised Machine Learning model, enabling real-time personalisation of rehabilitation exercise intensity for post-cardiac surgery patients.
Addresses the cybersecurity of connected industrial systems, developing modular secure-integration architectures, hybrid pro-active security models, and machine-learning methods for threat detection and automatic recovery in Industry 4.0 networks.
Targets the optimization of production processes through the joint integration of collaborative robots and AI technologies, including an AI Integration Score for equipment readiness assessment and an AI-driven Digital Twin for collaborative process monitoring.
Targets the optimization of automotive wire-harness production through collaborative robotics, AI-based perception (detection and 3D pose estimation), and a cell-level Digital Twin with a Human Digital Twin layer for ergonomic monitoring and dynamic task allocation.
