Institute for Human-Centered Artificial Intelligence (HAI)
Showing 51-100 of 188 Results
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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.
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Takako Fujioka
Associate Professor of Music
BioResearch topics include neural oscillations for auditory perception, auditory-motor coupling, brain plasticity in development and aging, and recovery from stroke with music-supported therapy.
Her post-doctoral and research-associate work at Rotman Research Institute in Toronto was supported by awards from the Canadian Institutes of Health Research. Her research continues to explore the biological nature of human musical ability by examining brain activities with non-invasive human neurophysiological measures such as magnetoencephalography (MEG) and electroencephalography (EEG). -
Francis Fukuyama
Olivier & Nomellini Senior Fellow in International Studies at the Freeman Spogli Institute for International Studies and Professor, by courtesy, of Political Science
Current Research and Scholarly InterestsDeveloping nations; governance; international political economy; nation-building and democratization; strategic and security issues
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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 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.
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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). -
Jens Hainmueller
Kimberly Glenn Professor and Professor of Political Science
BioJens Hainmueller is the Kimberly Glenn Professor in Political Science and Director of Graduate Studies of the Department of Political Science at Stanford University. He is the Faculty Co-Director of the Stanford Immigration Policy Lab that is focused on the design and evaluation of immigration and integration policies and programs.
His research interests include statistical methods, causal inference, immigration, and political economy. He has published over 65 articles, many of them in top general science journals (e.g. Science, Nature, PNAS) and top field journals in political science, statistics, economics, and business. His statistical methods are used by organizations to conduct causal inferences in various settings. He has also published multiple open source software packages. His research has received funding from organizations such as Schmidt Futures, the Robin Hood Foundation, the Robert Wood Johnson Foundation, the National Science Foundation, the National Institute of Health, and the National Bureau of Economic Research. His research has won various awards including the Gosnell Prize for Excellence in Political Methodology, the Warren Miller Prize, the Robert H. Durr award, and the Emerging Scholar award by the Society of Political Methodology. He was selected as an Andrew Carnegie Fellow and inducted as a Fellow of the Society of Political Methodology. He has received an honorary degree from the European University Institute (EUI).
Hainmueller received his PhD from Harvard University and also studied at the London School of Economics, Brown University, and the University of Tübingen. Before joining Stanford, he served on the faculty of the Massachusetts Institute of Technology. -
Eric Hanushek
Paul and Jean Hanna Senior Fellow at the Hoover Institution and Professor, by courtesy, of Education
BioEric Hanushek is the Paul and Jean Hanna Senior Fellow at the Hoover Institution of Stanford University. He is internationally recognized for his economic analysis of educational issues, and his research has broadly influenced education policy in both developed and developing countries. In recognition of his outstanding contributions to the field, he was awarded the prestigious Yidan Prize for Education Research in 2021. His extensive and well-cited body of work encompasses many pivotal topics within education, including class size reduction, school accountability, and teacher effectiveness. His pioneering exploration into teacher effectiveness, quantified through students' learning gains, laid the foundation for the widespread adoption of value-added measures in evaluating educators and institutions. His seminal book, The Knowledge Capital of Nations: Education and the Economics of Growth, establishes the close relationship between a nation's long-term economic growth and the skill levels of its populace. His scholarly contributions include twenty-six books and over 300 articles contributing to knowledge within the field. He is a Distinguished Graduate of the United States Air Force Academy and completed his Ph.D. in economics at the Massachusetts Institute of Technology. (https://hanushek.stanford.edu/)
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Gabriella M. Harari
Assistant Professor of Communication
BioGabriella Harari is an Assistant Professor in the Department of Communication at Stanford University, where she directs the Media and Personality Lab.
She studies how personality is expressed in the physical and digital contexts of everyday life. Much of her research is focused on understanding what digital technologies reveal about who we are, and how use of digital technologies shapes who we are. Her current projects analyze people’s everyday behavioral patterns (e.g., social interactions, mobility) and environmental contexts (e.g., places visited, social media platforms) to show how they are associated with individual differences in personality and well-being.
Harari takes an ecological approach to conducting her research, emphasizing the importance of studying people and their behavior in natural contexts. To that end, she conducts intensive longitudinal field studies and is interested in mobile sensing methods and analytic techniques that combine approaches from the social and computer sciences. For example, methodologies she uses in her work in include surveys, experience sampling, longitudinal modeling, mobile sensing, data mining, and machine learning.
Harari completed a Postdoctoral Fellowship and earned her PhD at the Department of Psychology at The University of Texas at Austin. She completed her BA in Psychology & Humanities from Florida International University, where she was also a Ronald E. McNair Scholar. Her work has been published in academic outlets such as Perspectives in Psychological Science, Journal of Personality and Social Psychology, and the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). Her work has also been supported by the National Science Foundation and Stanford HAI Seed Grant Awards. -
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 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.
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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.
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Jackelyn Hwang
Assistant Professor of Sociology
BioJackelyn Hwang is an Assistant Professor in the Department of Sociology and a faculty affiliate at the Center for Comparative Studies in Race and Ethnicity and the Urban Studies Program. Jackelyn’s main research interests are in the fields of urban sociology, race and ethnicity, immigration, and inequality. In particular, her research examines the relationship between how neighborhoods change and the persistence of neighborhood inequality by race and class in US cities. Her current projects focus on the causes and consequences of gentrification and developing automated methods for measuring neighborhood change using Google Street View imagery.
Jackelyn received her B.A.S. in Sociology and Mathematics from Stanford University and her Ph.D. in Sociology and Social Policy from Harvard University. After completing her Ph.D., she was a Postdoctoral Research Fellow in the Office of Population Research at Princeton University. Her research has been supported by the American Sociological Association, the Joint Center for Housing Studies, the National Science Foundation, among others. Her work has appeared in the American Sociological Review, Demography, Social Forces, and other academic journals. -
Daniel Imler
Clinical Associate Professor, Emergency Medicine
Clinical Associate Professor, PediatricsCurrent Research and Scholarly InterestsI am interested in understanding the impact of smart, agile clinical pathways to drive behavior change among providers.
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Ramesh Johari
Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering and of Computer Science
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).
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Amit Kaushal
Adjunct Professor, Bioengineering
BioAmit Kaushal, MD, PhD is Clinical Associate Professor of Medicine (Stanford-VA) and Adjunct Professor of Bioengineering at Stanford University. Dr. Kaushal's work spans clinical medicine, teaching, research, and industry.
He helped launch Stanford School of Engineering's undergraduate major in Biomedical Computation (bmc.stanford.edu) and has served as long-time director of the major. The major has graduated over 70 students since inception and was recently featured in Nature (https://go.nature.com/2P2UnRu).
His research interests are in utilizing health data in novel and ethical ways to improve the practice of medicine. He is a faculty executive member of Stanford's Partnership for AI-Assisted Care (aicare.stanford.edu). Recently, he has also been working with public health agencies to improve scale and speed of contact tracing for COVID-19.
He has previously held executive and advisory roles at startups working at the interface of technology and healthcare.
He continues to practice as an academic hospitalist.
Dr. Kaushal completed his BS (Biomedical Computation), MD, PhD (Biomedical Informatics), and residency training at Stanford. He is board-certified in Internal Medicine and Clinical Informatics. -
Monroe Kennedy III
Assistant Professor of Mechanical Engineering and, by courtesy, of Computer Science
Current Research and Scholarly InterestsMy research focus is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. My research can be divided into the following sub-categories: robotic assistants, connected devices and intelligent wearables. My Assistive Robotics and Manipulation lab focuses heavily on both the analytical and experimental components of assistive technology design.
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Khizer Khaderi MD, MPH
Clinical Associate Professor, Ophthalmology
BioDr. Khizer Khaderi is a Clinical Associate Professor at the Byers Eye Institute at Stanford University. Khaderi is the Founding Director of the Stanford Human Perception Laboratory (HPL) and the Stanford Vision Performance Center (VPC). He also serves as faculty at the Stanford Institute for Human-Centered AI and the Wu Tsai Human Performance Alliance (HPA)
Khaderi is a renowned Neuro-Ophthalmic surgeon, technologist and futurist. Dr. Khaderi is pioneering the field of Symbiotics, defined as the convergence of human science + computer science to design and develop human-centric technologies. Khaderi has extensive domain expertise in artificial intelligence (AI), spatial computing (virtual reality (VR), augmented reality (AR), mixed reality (MxR)), wearables, gaming, IoT, Web3, applied neuroscience, human factors, and human-machine interfaces/interaction. His research interests include developing personalized human intelligent systems based on the human brain and sensory systems, developing technologies to optimize human performance, and combining biological and computational principles to expand our capabilities in research, clinical practice, and everyday life. Dr. Khaderi's approach to advance research interests and develop practical applications for everyday use is building technology, companies and collaborative partnerships across academia and industry.
Dr. Khaderi’s experience across industry sectors include consumer electronics, gaming, retail, life science, sports/Esports health care, Pharma, e-commerce, to name a few. He has developed novel technologies in these areas, and generated multiple invention patents. Selected as a “40 under 40”, he contributed to President Obama’s Council of Advisors on Science and Technology regarding vision technology and the aging population. He also advises multiple companies, venture firms and organizations including the Global Esports Federation, Magic Leap, Riot Games, Intel, Activision, Unity, Epic Games, Google, FB, Microsoft, Apple, NBA, Aerie Pharma, the World Health Organization, and the World Bank. -
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.
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Jennifer King
HAI Privacy and Data Policy Fellow
Current Research and Scholarly InterestsI research information privacy from the user's perspective (HCI) across multiple domains, including: online commercial contexts, IoT/Ubicomp, human genetics. I conduct both theoretical and applied privacy research, with a focus on the impacts of law and policy on privacy. My dissertation research explored the effects of social structures (such as power differentials) on individuals' decisions to disclose personal information in commercial contexts.
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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).
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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.
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Michal Kosinski
Associate Professor of Organizational Behavior at the Graduate School of Business
BioPlease visit: http://www.michalkosinski.com/
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Anshul Kundaje
Associate Professor of Genetics
Current Research and Scholarly InterestsWe develop statistical and machine learning frameworks to learn predictive, dynamic and causal models of gene regulation from heterogeneous functional genomics data.
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Monica Lam
Kleiner Perkins, Mayfield, Sequoia Capital Professor in the School of Engineering and Professor, by courtesy, of Electrical Engineering
BioDr. Monica Lam is a Professor in the Computer Science Department at Stanford University, and the Faculty Director of the Stanford Open Virtual Assistant Laboratory. Dr. Monica Lam obtained her BS degree in computer science from University of British Columbia, and her PhD degree in computer science from Carnegie Mellon University in 1987. She joined Stanford in 1988.
Professor Lam's current research is on conversational virtual assistants with an emphasis on privacy protection. Her research uses deep learning to map task-oriented natural language dialogues into formal semantics, represented by a new executable programming language called ThingTalk. Her Almond virtual assistant, trained on open knowledge graphs and IoT API standards, can be easily customized to perform new tasks. She is leading an Open Virtual Assistant Initiative to create the largest, open, crowdsourced language semantics model to promote open access in all languages. Her decentralized Almond virtual assistant that supports fine-grain sharing with privacy has received Popular Science's Best of What's New Award in Security in 2019.
Prof. Lam is also an expert in compilers for high-performance machines. Her pioneering work of affine partitioning provides a unifying theory to the field of loop transformations for parallelism and locality. Her software pipelining algorithm is used in commercial systems for instruction level parallelism. Her research team created the first, widely adopted research compiler, SUIF. She is a co-author of the classic compiler textbook, popularly known as the “dragon book”. She was on the founding team of Tensilica, now a part of Cadence.
Dr. Lam is a Member of the National Academy of Engineering and an Association of Computing Machinery (ACM) Fellow. -
Eric Lambin
George and Setsuko Ishiyama Provostial Professor and Senior Fellow at the Woods Institute for the Environment
Current Research and Scholarly InterestsI study human-environment interactions in land systems by linking remote sensing, GIS and socio-economic data. I aim at better understanding causes and impacts of changes in tropical forests, drylands, and farming systems. I currently focus on land use transitions – i.e., the shift from deforestation (or land degradation) to reforestation (or land sparing for nature), – the influence of globalization on land use decisions, and the interactions between public and private governance of land use.
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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.
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Curtis Langlotz
Professor of Radiology (Thoracic Imaging), of Biomedical Informatics Research, of Biomedical Data Science and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsI am interested in the use of deep neural networks and other machine learning technologies to help radiologists detect disease and eliminate diagnostic errors. My laboratory is developing deep neural networks that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report to create large annotated image training sets for supervised machine learning experiments.
