Marcos Sobral

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About

Marcos Sobral is a researcher at the intersection of affective computing, human-robot interaction, and child psychology. His work centers on developing intelligent systems that can recognize and respond to human emotions, with a particular focus on applications in therapeutic settings. His most cited paper, "Hybrid Models for Facial Emotion Recognition in Children" (2023), introduces novel hybrid architectures that combine deep learning and traditional computer vision techniques to accurately detect emotional expressions in children. This contribution is especially significant for agent-mediated therapy, where remotely operated robots assist psychologists in conducting sessions with young patients. By enabling machines to interpret subtle facial cues, Sobral’s research helps bridge the gap between technological capability and clinical need, supporting more natural and effective human-robot interactions in sensitive contexts. Though early in its citation impact, this work reflects a growing trend toward integrating robotics and computer science into mental health care. Sobral’s contributions are paving the way for more empathetic, responsive therapeutic tools that can extend the reach of professional care to children in remote or underserved settings.