Our research at the Dependable Systems Design Lab spans a diverse and interdisciplinary range of domains at the intersection of hardware / software and intelligent systems. We develop advanced machine learning (ML) and deep machine learning (DML) algorithms for biomedical signal processing, focusing on the detection of ECG arrhythmias, sleep apnea, and the estimation of heart biological age.
In parallel, we investigate cutting-edge hardware security solutions, including the detection and prevention of hardware Trojans, logic locking techniques, and resilience against ML-based attacks on integrated circuits. Our team also explores AI-driven smart surveillance systems for real-time video monitoring and threat detection. In the automotive domain, we work on robust computer vision AI-based algorithms for self-driving cars, including object detection and multi-object tracking.
Additionally, we emphasize the design, verification and implementation of reliable and energy-efficient digital circuits to ensure high performance and low power consumption in modern embedded systems.