School of Humanities and Sciences
Showing 101-200 of 322 Results
-
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.
-
James Gross
Ernest R. Hilgard Professor, Professor of Psychology and, by courtesy, of Philosophy
Current Research and Scholarly InterestsI am interested in emotion and emotion regulation. My research employs behavioral, physiological, and brain measures to examine emotion-related personality processes and individual differences. My current interests include emotion coherence, specific emotion regulation strategies (reappraisal, suppression), automatic emotion regulation, and social anxiety.
-
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
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.
-
Keren Haroush
Assistant Professor of Neurobiology
Current Research and Scholarly InterestsOur laboratory studies the mechanisms by which highly complex behaviors are mediated at the neuronal level, mainly focusing on the example of dynamic social interactions and the neural circuits that drive them. From dyadic interactions to group dynamics and collective decision making, the lab seeks a mechanistic understanding for the fundamental building blocks of societies, such as cooperation, empathy, fairness and reciprocity.
-
Robert Hawkins
Assistant Professor of Linguistics
BioI direct the Social Interaction & Language (SoIL) Lab at Stanford University. We're interested in the cognitive mechanisms that allow people to flexibly communicate, collaborate, and coordinate with one another. We work on these problems using large-scale, multi-player web experiments and computational models of language and social reasoning.
-
Pamela Hinds
Rodney H. Adams Professor in the School of Engineering, Fortinet Founders Chair of the Department of Management Science and Engineering and Professor of Management Science and Engineering
BioPamela J. Hinds is Rodney H. Adams Chair and Fortinet Founders Chair and Professor of Management Science & Engineering, Co-Director of the Center on Work, Technology, and Organization and on the Director's Council for the Hasso Plattner Institute of Design. She studies the effect of technology on teams, collaboration, and innovation. Pamela has conducted extensive research on the dynamics of cross-boundary work teams, particularly those spanning national borders. She explores issues of culture, language, identity, conflict, and the role of site visits in promoting knowledge sharing and collaboration. She has published extensively on the relationship between national culture and work practices, particularly exploring how work practices or technologies created in one location are understood and employed at distant sites. Pamela also has a body of research on human-robot interaction in the work environment and the dynamics of human-robot teams. Most recently, Pamela has been looking at the changing nature of work in the face of emerging technologies, including the nature of coordination in open innovation, changes in work and organizing resulting from 3D-printing, and the work of data analysts. Her research has appeared in journals such as Organization Science, Research in Organizational Behavior, Academy of Management Journal, Academy of Management Annals, Academy of Management Discoveries, Human-Computer Interaction, Journal of Applied Psychology, Journal of Experimental Psychology: Applied, and Organizational Behavior and Human Decision Processes. Pamela is a Senior Editor of Organization Science. She is also co-editor with Sara Kiesler of the book Distributed Work (MIT Press). Pamela holds a Ph.D. in Organizational Science and Management from Carnegie Mellon University.
-
Daniel Ho
William Benjamin Scott & Luna M. Scott Professor of Law, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, at the Stanford Institute for HAI and Professor, by courtesy, of Computer Science
BioDaniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, Professor of Computer Science (by courtesy), Senior Fellow at Stanford's Institute for Human-Centered Artificial Intelligence, and Senior Fellow at the Stanford Institute for Economic Policy Research at Stanford University. He is a Faculty Fellow at the Center for Advanced Study in the Behavioral Sciences and is Director of the Regulation, Evaluation, and Governance Lab (RegLab). Ho serves on the National Artificial Intelligence Advisory Commission (NAIAC), advising the White House on artificial intelligence, as Senior Advisor on Responsible AI at the U.S. Department of Labor, and as a Public Member of the Administrative Conference of the United States (ACUS). He received his J.D. from Yale Law School and Ph.D. from Harvard University and clerked for Judge Stephen F. Williams on the U.S. Court of Appeals, District of Columbia Circuit.
-
Susan Holmes
Professor of Statistics, Emerita
Current Research and Scholarly InterestsOur lab has been developing tools for the analyses of complex data structures, extending work on multivariate data to structured multitable table that include graphs, networks and trees as well as categorical and continuous measurements.
We created and support the Bioconductor package phyloseq for the analyses of microbial ecology data from the microbiome. We have specialized in developing interactive graphical visualization tools for doing reproducible research in biology. -
Oussama Khatib
Weichai Professor and Professor, by courtesy, of Electrical Engineering
BioRobotics research on novel control architectures, algorithms, sensing, and human-friendly designs for advanced capabilities in complex environments. With a focus on enabling robots to interact cooperatively and safely with humans and the physical world, these studies bring understanding of human movements for therapy, athletic training, and performance enhancement. Our work on understanding human cognitive task representation and physical skills is enabling transfer for increased robot autonomy. With these core capabilities, we are exploring applications in healthcare and wellness, industry and service, farms and smart cities, and dangerous and unreachable settings -- deep in oceans, mines, and space.
-
Brian Knutson
Professor of Psychology
Current Research and Scholarly InterestsMy lab and I seek to elucidate the neural basis of emotion (affective neuroscience), and explore implications for decision-making (neuroeconomics) and psychopathology (neurophenomics).
-
Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics and, by courtesy, of Computer Science
BioMykel Kochenderfer is Associate Professor of Aeronautics and Astronautics at Stanford University. Prior to joining the faculty, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance, with his early work leading to the establishment of the ACAS X program. He received a Ph.D. from the University of Edinburgh and B.S. and M.S. degrees in computer science from Stanford University. Prof. Kochenderfer is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and other aerospace applications where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. He is an author of "Decision Making under Uncertainty: Theory and Application" (2015), "Algorithms for Optimization" (2019), and "Algorithms for Decision Making" (2022), all from MIT Press. He is a third generation pilot.
-
Michal Kosinski
Associate Professor of Organizational Behavior at the Graduate School of Business
BioPlease visit: http://www.michalkosinski.com/
-
James Landay
Denning Co-Director (Acting) of Stanford HAI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsLanday's current research interests include Technology to Support Behavior Change (especially for health and sustainability), Demonstrational User Interfaces, Mobile & Ubiquitous Computing, Cross-Cultural Interface Design, Human-Centered AI, and User Interface Design Tools. He has developed tools, techniques, and a top professional book on Web Interface Design.
-
Victor R. Lee
Associate Professor of Education
Current Research and Scholarly InterestsAI literacy, data literacy, quantified self, maker education, conceptual change in science, elementary computer science education
-
Mark Lemley
William Neukom Professor of Law and Senior Fellow at the Stanford Institute for Economic Policy Research
Current Research and Scholarly Interestsintellectual property, Internet, and antitrust law; law and AI/robotics
-
Marc Levoy
VMware Founders Professor in Computer Science and Professor of Electrical Engineering, Emeritus
BioLevoy's current interests include the science and art of photography, computational photography, light field sensing and display, and applications of computer graphics in microscopy and biology.
-
Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for HAI
BioChristopher Manning is the inaugural Thomas M. Siebel Professor in Machine Learning in the Departments of Linguistics and Computer Science at Stanford University, Director of the Stanford Artificial Intelligence Laboratory (SAIL), and an Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence (HAI). From 2010, Manning pioneered Natural Language Understanding and Inference using Deep Learning, with impactful research on sentiment analysis, paraphrase detection, the GloVe model of word vectors, attention, neural machine translation, question answering, self-supervised model pre-training, tree-recursive neural networks, machine reasoning, dependency parsing, and summarization, work for which he has received two ACL Test of Time Awards and the IEEE John von Neumann Medal (2024). He earlier led the development of empirical, probabilistic approaches to NLP, computational linguistics, and language understanding, defining and building theories and systems for Natural Language Inference, syntactic parsing, machine translation, and multilingual language processing, work for which he won ACL, Coling, EMNLP, and CHI Best Paper Awards. In NLP education, Manning coauthored foundational textbooks on statistical approaches to NLP (Manning and Schütze 1999) and information retrieval (Manning, Raghavan, and Schütze, 2008), and his online CS224N Natural Language Processing with Deep Learning course videos have been watched by hundreds of thousands. In linguistics, Manning is a principal developer of Stanford Dependencies and Universal Dependencies, and has authored monographs on ergativity and complex predicates. He is the founder of the Stanford NLP group (@stanfordnlp) and was an early proponent of open source software in NLP with Stanford CoreNLP and Stanza. He is an ACM Fellow, a AAAI Fellow, and an ACL Fellow, and a Past President of the ACL (2015). Manning has a B.A. (Hons) from The Australian National University, a Ph.D. from Stanford in 1994, and an Honorary Doctorate from U. Amsterdam in 2023. He held faculty positions at Carnegie Mellon University and the University of Sydney before returning to Stanford.
-
Ellen Markman
IBM Provostial Professor
BioMarkman’s research interests include the relationship between language and thought; early word learning; categorization and induction; theory of mind and pragmatics; implicit theories and conceptual change, and how theory-based explanations can be effective interventions in health domains.
-
Jay McClelland
Lucie Stern Professor in the Social Sciences, Professor of Psychology and, by courtesy, of Linguistics and of Computer Science
Current Research and Scholarly InterestsMy research addresses topics in perception and decision making; learning and memory; language and reading; semantic cognition; and cognitive development. I view cognition as emerging from distributed processing activity of neural populations, with learning occurring through the adaptation of connections among neurons. A new focus of research in the laboratory is mathematical cognition and reasoning in humans and contemporary AI systems based on neural networks.
-
Raymond McDermott
Professor of Education, Emeritus
Current Research and Scholarly InterestsInteraction analysis and social structure; the political economy of learning; writing systems; educational and psychological anthropology.
-
Vinod Menon
Rachael L. and Walter F. Nichols, MD, Professor and Professor, by courtesy, of Education and of Neurology and Neurological Sciences
Current Research and Scholarly InterestsEXPERIMENTAL, CLINICAL AND THEORETICAL SYSTEMS NEUROSCIENCE
Cognitive neuroscience; Systems neuroscience; Cognitive development; Psychiatric neuroscience; Functional brain imaging; Dynamical basis of brain function; Nonlinear dynamics of neural systems. -
Oscar Daniel Mier
Masters Student in Symbolic Systems, admitted Autumn 2022
BioOscar Daniel Mier, a driven neuroscience professional and Master of Science candidate in Symbolic Systems at Stanford University, exemplifies unwavering dedication to neuroscience, neuroimaging, and the welfare of veterans. With a Bachelor of Science in Neuroscience from the University of California, Riverside, and graduate training in Neuroimaging and Informatics from the University of Southern California, Oscar's academic journey has propelled him through a multifaceted career. His experience includes working as a Clinical Research Coordinator at the Etkin Lab, the United States Marine Corps, and a Site Lead Clinical Research Coordinator at the U.S. Department of Veteran Affairs Palo Alto Healthcare System.
Oscar's passion for helping others shines through his work as a Mobile Training Team S.T.E.M. Fellow with the Warrior-Scholar Project, where he tutored and mentored student veterans and active service members and coordinated academic boot camps at prestigious universities. In his most recent position as a Technical Solutions Engineer at Alto Neuroscience, Oscar managed neuroimaging data and trained clinicians on clinical study paradigms. As he continues his academic journey at Stanford, Oscar brings his extensive experience, expertise, and unwavering commitment to the forefront, poised to make a lasting impact in the field of neuroscience and the lives of veterans. -
Holden Moore
Undergraduate, Symbolic Systems
BioStanford University undergraduate student majoring in symbolic systems with a concentration in neuroscience. Pursuing an interdisciplinary degree across diverse fields of study including computer science, mathematics, neuroscience, statistics, philosophy, and psychology.
