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Kaya de Barbaro is an Associate Professor at the University of Texas at Austin, focusing on the intersection of developmental clinical psychology and computer science engineering. Her current research explores maternal mental health and infant social-emotional development, with a particular interest in how everyday interactions contribute to infant attachment and self-regulation, influenced by maternal depression and anxiety. Her lab employs mobile sensing technologies to capture real-time dynamics of mother-infant interactions in natural home environments, utilizing various data types including audio recordings and physiological metrics. This data aids in understanding social-emotional development and aims to develop timely interventions for new mothers. De Barbaro's work emphasizes the use of machine learning algorithms to analyze complex datasets, providing insights into parental behaviors and the implications for infant mental health.
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