Symbolic Systems
Showing 91-100 of 288 Results
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Hyowon Gweon
Associate Professor of Psychology
BioHyowon (Hyo) Gweon (she/her) is an Associate Professor in the Department of Psychology. As a leader of the Social Learning Lab, Hyo is broadly interested in how humans learn from others and help others learn: What makes human social learning so powerful, smart, and distinctive? Taking an interdisciplinary approach that combines developmental, computational, and neuroimaging methods, her research aims to explain the cognitive underpinnings of distinctively human learning, communication, and prosocial behaviors.
Hyo received her PhD in Cognitive Science (2012) from MIT, where she continued as a post-doc before joining Stanford in 2014. Honors and awards include: Richard E. Guggenhime Faculty Scholar (2020) and a David Huntington Dean's Faculty Scholar (2019) from Stanford; CDS Steve Reznick Early Career Award (2022), APS Janet Spence Award for Transformative Early Career Contributions (2020), Jacobs Early Career Fellowship (2020), James S. McDonnell Scholar Award for Human Cognition (2018), APA Dissertation Award (2014), and Marr Prize (best student paper, Cognitive Science Society 2010). -
Nicholas Haber
Assistant Professor of Education
Current Research and Scholarly InterestsI use AI models of of exploratory and social learning in order to better understand early human learning and development, and conversely, I use our understanding of early human learning to make robust AI models that learn in exploratory and social ways. Based on this, I develop AI-powered learning tools for children, geared in particular towards the education of those with developmental issues such as the Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder, in the mold of my work on the Autism Glass Project. My formal graduate training in pure mathematics involved extending partial differential equation theory in cases involving the propagation of waves through complex media such as the space around a black hole. Since then, I have transitioned to the use of machine learning in developing both learning tools for children with developmental disorders and AI and cognitive models of learning.
