Stanford University


Showing 31-40 of 104 Results

  • Michael Frank

    Michael Frank

    Benjamin Scott Crocker Professor of Human Biology and Professor, by courtesy, of Linguistics

    Current Research and Scholarly InterestsHow do we learn to communicate using language? I study children's language learning and how it interacts with their developing understanding of the social world. I use behavioral experiments, computational tools, and novel measurement methods like large-scale web-based studies, eye-tracking, and head-mounted cameras.

  • Justin Gardner

    Justin Gardner

    Associate Professor of Psychology

    Current Research and Scholarly InterestsHow does neural activity in the human cortex create our sense of visual perception? We use a combination of functional magnetic resonance imaging, computational modeling and analysis, and psychophysical measurements to link human perception to cortical brain activity.

  • Michael Genesereth

    Michael Genesereth

    Associate Professor of Computer Science

    BioGenesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the director of the Logic Group at Stanford and the founder and research director of CodeX - the Stanford Center for Legal Informatics.

  • Deborah M Gordon

    Deborah M Gordon

    Professor of Biology

    Current Research and Scholarly InterestsProfessor Deborah M Gordon studies the evolutionary ecology of collective behavior. Ant colonies operate without central control, using local interactions to regulate colony behavior.

  • Kalanit Grill-Spector

    Kalanit Grill-Spector

    Susan S. and William H. Hindle Professor in the School of Humanities and Sciences

    Current Research and Scholarly InterestsFor humans, recognition is a natural, effortless skill that occurs within a few hundreds of milliseconds, yet it is one of the least understood aspects of visual perception. Our research utilizes functional imaging (fMRI),diffusion weighted imaging (DWI), computational techniques, and behavioral methods to investigate the neural mechanisms underlying visual recognition in humans. We also examine the development of these mechanisms from childhood to adulthood as well as between populations.

  • Hyowon Gweon

    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. She has been named as a Richard E. Guggenhime Faculty Scholar (2020) and a David Huntington Dean's Faculty Scholar (2019); she is a recipient of the 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

    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.