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About

Giovanna Castellano is a multidisciplinary researcher whose work spans social robotics, human-robot interaction, fuzzy control systems, and intelligent learning technologies. Over more than two decades of scholarship, she has made significant contributions to the development of autonomous and socially intelligent robotic systems, with her earliest work in the late 1990s establishing foundational methods for automatic fuzzy rule generation in reactive robot controllers — an area she continued to refine into the 2000s. Her most impactful recent research centers on the Pepper robot as an educational and therapeutic platform. Her 2021 study, "PeppeRecycle," garnered 61 citations by demonstrating how social robots can effectively reshape children's attitudes toward recycling through gamified interaction — a theme she has pursued across multiple publications since 2019. Equally notable is her work applying social robotics to cognitive stimulation training and elderly care, with papers exploring emotion detection and empathy-driven robot design for aging populations. Castellano has also contributed to museum visitor engagement through robotic guides and to biometric security through neural network-based signature verification. Her body of work reflects a consistent commitment to making intelligent systems more human-centered, empathetic, and practically impactful across education, healthcare, and public life.