Thesis topics I coordinate, for both bachelor's students and PhD candidates. I supervise around 10 bachelor theses each year.
Topics available for undergraduate students in robotics, computer vision, AI, and embedded systems.
Doctoral research directions I coordinate.
Development of a Digital Twin architecture for real-time monitoring of an industrial robotic line; AI-based predictive maintenance models for anomaly detection and failure anticipation; operational optimization to reduce downtime; and intelligent cybersecurity/resilience mechanisms for industrial robotic lines.
Interpretable hybrid models for fixed-base robots combining classical physics models with AI-based correction; online self-modelling of kinematic/dynamic deviations; explainable residual learning for non-linearities, friction, and backlash; adaptive control based on uncertainty estimation; experimental validation on a lab robotic platform.
A framework combining AI-based cybersecurity mechanisms with functional safety strategies for autonomous drone fleets, including Trustworthy AI; real-time threat detection and mitigation on resource-constrained microcontroller platforms; and rigorous testing and validation in realistic scenarios.