Trustworthy Autonomous System

Trustworthy Autonomous Systems (TAS) research focuses on developing autonomous systems that are reliable, safe, and ethically sound. Current efforts concentrate on improving system dependability through formal methods, fault injection techniques, and Bayesian deep learning to better model and manage uncertainty within complex AI components. This work is crucial for ensuring the safe and responsible deployment of autonomous systems across various sectors, impacting both the scientific understanding of AI safety and the practical application of these technologies in real-world scenarios. Addressing privacy concerns, particularly in vision-based systems, is also a key area of investigation.