Sandra Clara Gadanho

Papers

Total Citations

159

H-Index

About

Sandra Clara Gadanho is a pioneering researcher in the intersection of affective computing, autonomous robotics, and machine learning, whose work has significantly shaped our understanding of how emotion-inspired mechanisms can enhance artificial intelligence. Her research centers on a provocative and influential question: can emotions make robots smarter and more adaptive? Gadanho's most impactful contribution, "Robot Learning Driven by Emotions" (2001), garnered 89 citations and introduced a non-symbolic emotion model embedded in a recurrent neural architecture, demonstrating that emotion-like processes could guide learning in simulated robotic systems. This work laid important groundwork for affective robotics as a legitimate research domain. Her closely related paper on emotion-triggered learning (2001, 46 citations) further explored how emotional signals could determine when a robot should interrupt or redirect its behavior — a subtle but critical challenge in autonomous control. Beginning as early as 1998, Gadanho was already interrogating the role of self-motivation in robotic autonomy, distinguishing true autonomy from mere automaticity. Her later work on multi-goal robot tasks extended these ideas into more complex, real-world-inspired scenarios. Collectively, her contributions established a compelling case that emotions are not just metaphors for machine behavior, but functional tools for building genuinely adaptive autonomous systems.