Independent Labs, Institutes, and Centers (Dean of Research)
Showing 1-17 of 17 Results
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Surya Ganguli
Associate Professor of Applied Physics, Senior Fellow at the Stanford Institute for HAI and Associate Professor, by courtesy, of Neurobiology and of Electrical Engineering
Current Research and Scholarly InterestsTheoretical / computational neuroscience
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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.
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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.
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Michael Gensheimer
Clinical Associate Professor, Radiation Oncology - Radiation Therapy
Current Research and Scholarly InterestsIn addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.
I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data. -
Ashish Goel
Professor of Management Science and Engineering and, by courtesy, of Computer Science
BioAshish Goel is a Professor of Management Science and Engineering and (by courtesy) Computer Science at Stanford University. He received his PhD in Computer Science from Stanford in 1999, and was an Assistant Professor of Computer Science at the University of Southern California from 1999 to 2002. His research interests lie in the design, analysis, and applications of algorithms.
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Henry T. (Hank) Greely
Deane F. and Kate Edelman Johnson Professor of Law and, Professor, by courtesy, of Genetics
Current Research and Scholarly InterestsSince 1992 my work has concentrated on ethical, legal, and social issues in the biosciences. I am particularly active on issues arising from neuroscience, human genetics, and stem cell research, with cross-cutting interests in human research protections, human biological enhancement, and the future of human reproduction.
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David Grusky
Edward Ames Edmonds Professor of Economics and Senior Fellow at the Stanford Institute for Economic Policy Research
BioDavid B. Grusky is Barbara Kimball Browning Professor in the School of Humanities and Sciences, Director of the Stanford Center on Poverty and Inequality, and coeditor of Pathways Magazine. His research addresses the changing structure of late-industrial inequality and addresses such topics as (a) the role of rent-seeking and market failure in explaining the takeoff in income inequality, (b) the amount of economic and social mobility in the U.S. and other high-inequality countries (with a particular focus on the “Great Gatsby” hypothesis that opportunities for social mobility are declining), (c) the role of essentialism in explaining the persistence of extreme gender inequality, (d) the forces behind recent changes in the amount of face-to-face and online cross-class contact, and (e) the putative decline of big social classes. He is also involved in projects to improve the country’s infrastructure for monitoring poverty, inequality, and mobility by exploiting administrative and other forms of “big data” more aggressively. His recent books include Social Stratification (2014), Occupy the Future (2013), The New Gilded Age (2012), The Great Recession (2011), The Inequality Reader (2011), and The Inequality Puzzle (2010).
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Leonidas Guibas
Paul Pigott Professor of Engineering and Professor, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsGeometric and topological data analysis and machine learning. Algorithms for the joint analysis of collections of images, 3D models, or trajectories. 3D reconstruction.
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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. 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).
