Georgios Sopidis specializes in machine learning, computer vision, sensor fusion, and human-robot interaction (HRI), with a strong focus on developing AI-driven perception solutions for industrial settings. His work bridges the gap between human and machine perception to enable smarter, more collaborative production systems.

He holds a PhD in Computer Science from Johannes Kepler University Linz, where his doctoral research focused on human activity recognition (HAR) in industrial assembly environments, including deep learning approaches for weakly supervised learning and wearable sensor data analysis.