School of Humanities and Sciences
Showing 21-40 of 105 Results
Professor of French and Italian and, by courtesy, of Political ScienceOn Leave from 01/01/2022 To 08/31/2022
BioProfessor Jean-Pierre Dupuy is a Professor of Social and Political Philosophy at the École Polytechnique, Paris. He is the Director of research at the C.N.R.S. (Philosophy) and the Director of C.R.E.A. (Centre de Recherche en Épistémologie Appliquée), the philosophical research group of the École Polytechnique, which he founded in 1982. At Stanford University, he is a researcher at the Study of Language and Information (C.S.L.I.) Professor Dupuy is by courtesy a Professor of Political Science.
In his book The Mechanization of the Mind, Jean-Pierre Dupuy explains how the founders of cybernetics laid the foundations not only for cognitive science, but also artificial intelligence, and foreshadowed the development of chaos theory, complexity theory, and other scientific and philosophical breakthroughs.
Adjunct Professor, Psych/Public Mental Health & Population Sciences
BioDavid Eagleman is a neuroscientist, bestselling author, and Guggenheim Fellow. Dr. Eagleman’s areas of research include sensory substitution, time perception, vision, and synesthesia. He also studies the intersection of neuroscience with the legal system, and in that capacity he directs the non-profit Center for Science and Law. Eagleman is the writer and presenter of The Brain, an Emmy-nominated television series on PBS and BBC. He is the author of 8 books, including Livewired, The Runaway Species, The Brain, Incognito, and Wednesday is Indigo Blue. He is also the author of a widely adopted textbook on cognitive neuroscience, Brain and Behavior. His internationally bestselling book of literary fiction, SUM, has been translated into 32 languages, turned into two operas, and named a Best Book of the Year by Barnes and Noble. Dr. Eagleman has been a TED speaker, a guest on the Colbert Report, and profiled in the New Yorker magazine. He has launched several neuroscience companies from his research, including Neosensory and BrainCheck.
Albert Ray Lang Professor, Emerita
BioThe goal of my research is to understand the social meaning of linguistic variation. In order to do this, I pursue my sociolinguistic work in the context of in-depth ethnographic fieldwork, focusing on the relation between variation, linguistic style, social identity and social practice.
Gender has been the big misunderstood in studies of sociolinguistic variation - in spite of the fact that some of the most exciting intellectual developments over the past decades have been in theories of gender and sexuality ... so I have been spending a good deal of time working on language and gender as well.
Since adolescents and preadolescents are the movers and shakers in linguistic change, I concentrate on this age group, and much of my research takes place in schools. The institutional research site has made me think a good deal about learning and education, but particularly about the construction of adolescence in American society.
Johannes C. Eichstaedt
Assistant Professor (Research) of Psychology
Current Research and Scholarly InterestsI use large-scale language analyses and machine learning to characterize disease risk, measure subjective well-being and mental health of populations, and enrich and test psychological theory. I focus on applications of these methods that inform public health and public policy, and to create health systems that are more responsive to mental illness.
Josephine Knotts Knowles Professor of Human Biology, Emerita
Current Research and Scholarly InterestsWorking with English- and Spanish-learning children from diverse socioeconomic and cultural backgrounds, our research examines the importance of early language experience in supporting language development. We are deeply involved in community-based research in San Jose, designing an innovative parent-engagement program for low-resource Latino families with young children. We are also conducting field studies of beliefs about child development and caregiver-child interaction in rural villages in Senegal. A central goal of this translational research is to help parents understand their vital role in facilitating children’s language and cognitive growth.
Assistant Professor of Computer Science and of Electrical Engineering
BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
Assistant Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsHuman Computer Interaction, Haptics, Robotics, Human Centered Design
David and Lucile Packard Foundation Professor of Human Biology
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.
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.
Associate Professor of Computer Science and, by courtesy, of Law
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
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.
Professor of Psychology
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.
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).
Assistant Professor of Education and, by courtesy, of Computer Science
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.