Institute for Human-Centered Artificial Intelligence (HAI)
Showing 101-120 of 187 Results
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James Landay
Denning Co-Director (Acting) of Stanford Institute for Human-Centered AI, Anand Rajaraman and Venky Harinarayan Professor and Senior Fellow at the Stanford Institute for Human-Centered AI
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
Senior Associate Vice Provost for Research, Professor of Radiology (Integrative Biomedical Imaging Informatics), of Medicine (BMIR), of Biomedical Data Science and Senior Fellow at the Stanford Institute for Human-Centered AI
Current Research and Scholarly InterestsMy laboratory develops machine learning methods to help physicians detect disease and eliminate diagnostic errors. My laboratory is developing neural network systems that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report for contrastive learning and other multi-modal methods that improve the accuracy and capability of machine learning systems.
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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
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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
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Jure Leskovec
Professor of Computer Science
BioJure Leskovec is Professor of Computer Science at Stanford University. He is affiliated with the Stanford AI Lab, Machine Learning Group and the Center for Research on Foundation Models. In the past, he served as a Chief Scientist at Pinterest and was an investigator at Chan Zuckerberg BioHub. Leskovec recently pioneered the field of Graph Neural Networks and co-authored PyG, the most widely-used graph neural network library. Research from his group has been used by many countries to fight COVID-19 pandemic, and has been incorporated into products at Facebook, Pinterest, Uber, YouTube, Amazon, and more.
His research received several awards including Microsoft Research Faculty Fellowship in 2011, Okawa Research award in 2012, Alfred P. Sloan Fellowship in 2012, Lagrange Prize in 2015, and ICDM Research Contributions Award in 2019. His research contributions have spanned social networks, data mining and machine learning, and computational biomedicine with the focus on drug discovery. His work has won 12 best paper awards and 5 10-year test of time awards at a premier venues in these research areas.
Leskovec received his bachelor's degree in computer science from University of Ljubljana, Slovenia, PhD in machine learning from Carnegie Mellon University and postdoctoral training at Cornell University. -
Margaret Levi
Professor of Political Science and Senior Fellow at the Freeman Spogli Institute for International Studies, Emerita
BioMargaret Levi is Emerita Professor of Political Science, Senior Fellow, Center on Democracy, Development and the Rule of Law, Freeman Spogli Institute for International Studies, the former Sara Miller McCune Director and current Faculty Fellow of the Center for Advanced Study in the Behavioral Sciences (CASBS), and co-director of the Ethics and Society Review, Stanford University. She is Jere L. Bacharach Professor Emerita of International Studies in the Department of Political Science at the University of Washington. She held the Chair in Politics, the United States Studies Centre at the University of Sydney, 2009-13. At the University of Washington, she was director of the CHAOS (Comparative Historical Analysis of Organizations and States) Center and formerly the Harry Bridges Chair and Director of the Harry Bridges Center for Labor Studies.
Levi is the winner of the 2019 Johan Skytte Prize and 2020 Falling Walls Prize for Breakthrough of the Year in Social Sciences and Humanities. She became a fellow of the National Academy of Sciences in 2015, the British Academy in 2022, the American Academy of Arts and Sciences in 2001, the American Academy of Political and Social Science in 2017, and the American Philosophical Society in 2018. She was a John Simon Guggenheim Fellow in 2002. She served as president of the American Political Science Association from 2004 to 2005. She is the recipient of the 2014 William H. Riker Prize for Political Science. In 2019 she received an honorary doctorate from Universidad Carlos III de Madrid, 2019.
Levi is the author or coauthor of numerous articles and six books, including Of Rule and Revenue (University of California Press, 1988); Consent, Dissent, and Patriotism (Cambridge University Press, 1997); Analytic Narratives (Princeton University Press, 1998); Cooperation Without Trust? (Russell Sage, 2005), In the Interest of Others (Princeton, 2013), and A Moral Political Economy (Cambridge, 2021). She explores how organizations and governments provoke member willingness to act beyond material interest.
She was the general editor of Cambridge Studies in Comparative Politics. She is co-general editor of the Annual Review of Political Science and on the editorial board of PNAS.. Levi serves on the boards of the: Berggruen Institute: Center for Advanced Studies in the Social Sciences (CEACS) in Madrid; Research Council of the Canadian Institute for Advanced Research (CIFAR), and CORE Economics. Levi and her husband, Robert Kaplan, are avid collectors of Australian Aboriginal art. Ancestral Modern, an exhibition drawn from their collection, was on view at the Seattle Art Museum (SAM) in 2012. Yale University Press and SAM co-published the catalog.
Her fellowships include the Woodrow Wilson in 1968, German Marshall in 1988-9, and the Center for Advanced Study of the Behavioral Sciences in 1993-1994. She has lectured and been a visiting fellow at the Australian National University, the European University Institute, the Max Planck Institute in Cologne, the Juan March Institute, the Budapest Collegium, Cardiff University, Oxford University, Bergen University, and Peking University. She was a Phi Beta Kappa Visiting Scholar in 2005-6. She periodically serves as a consultant to the World Bank. -
Fei-Fei Li
Sequoia Capital Professor, Denning Co-Director (On Leave) Stanford Institute for Human-Centered AI, Senior Fellow at HAI and Professor, by courtesy, of Operations, Information and Technology at the Graduate School of Business
On Partial Leave from 01/01/2024 To 12/31/2025Current Research and Scholarly InterestsAI, Machine Learning, Computer Vision, Robotics, AI+Healthcare, Human Vision
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Ron Li
Clinical Associate Professor, Medicine
BioRon Li is a Clinical Associate Professor of Medicine in the Division of Hospital Medicine and Center for Biomedical Informatics Research at Stanford University School of Medicine. As the Medical Informatics Director for Digital Health at Stanford Health Care, he provides medical and informatics direction for the health system's enterprise digital health portfolio, including expanding digital referral networks and virtual care modalities. He is the co-founder and Director for the Stanford Emerging Applications Lab (SEAL), which helps clinicians and staff build ideas into novel digital products that are prototyped and tested for care delivery at Stanford Health Care.
Ron's academic interests focus on the "delivery science" of new technological capabilities such as digital and artificial intelligence in healthcare and how to design, implement, and evaluate new tech enabled models of care delivery. Ron's work spans across multiple disciplines, including clinical medicine, data science, digital health, information technology, design thinking, process improvement, and implementation science. He has consulted for various companies in the digital health and artificial intelligence space. He is an attending physician on the inpatient medicine teaching service at Stanford Hospital and is the Associate Program Director for the Stanford Clinical Informatics Fellowship. -
Percy Liang
Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for Human-Centered AI, and Associate Professor, by courtesy, of Statistics
BioPercy Liang is an Associate Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011) and the director of the Center for Research on Foundation Models (CRFM). He is currently focused on making foundation models (in particular, language models) more accessible through open-source and understandable through rigorous benchmarking. In the past, he has worked on many topics centered on machine learning and natural language processing, including robustness, interpretability, human interaction, learning theory, grounding, semantics, and reasoning. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and paper awards at ACL, EMNLP, ICML, COLT, ISMIR, CHI, UIST, and RSS.
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C. Karen Liu
Professor of Computer Science
BioC. Karen Liu is a professor in the Computer Science Department at Stanford University. Prior to joining Stanford, Liu was a faculty member at the School of Interactive Computing at Georgia Tech. She received her Ph.D. degree in Computer Science from the University of Washington. Liu's research interests are in computer graphics and robotics, including physics-based animation, character animation, optimal control, reinforcement learning, and computational biomechanics. She developed computational approaches to modeling realistic and natural human movements, learning complex control policies for humanoids and assistive robots, and advancing fundamental numerical simulation and optimal control algorithms. The algorithms and software developed in her lab have fostered interdisciplinary collaboration with researchers in robotics, computer graphics, mechanical engineering, biomechanics, neuroscience, and biology. Liu received a National Science Foundation CAREER Award, an Alfred P. Sloan Fellowship, and was named Young Innovators Under 35 by Technology Review. In 2012, Liu received the ACM SIGGRAPH Significant New Researcher Award for her contribution in the field of computer graphics.
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Matthew Lungren
Adjunct Professor, Biomedical Data Science
BioDr. Lungren is Chief Scientific Officer for Microsoft Health & Life Sciences where he focuses on translating cutting edge technology, including generative AI and cloud services, into innovative healthcare applications. As a physician and clinical machine learning researcher, he maintains collaborative research and teaching roles as adjunct professor at Stanford University.
Prior to joining Microsoft, Dr Lungren was a clinical interventional radiologist and research faculty at Stanford University Medical School where he led the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). He later served as Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare, focusing on business development for clinical machine learning technologies in the public cloud.
His scientific work has led to more than 200 publications, including work on multi-modal data fusion models for healthcare applications, new computer vision and natural language processing approaches for healthcare specific domains, opportunistic screening with machine learning for public health applications, open medical data as public good, prospective clinical trials for clinical AI translation, and application of generative AI in healthcare. He has served as advisor for early stage startups and large fortune-500 companies on healthcare AI technology development and go-to-market strategy. Dr. Lungren's work has been featured in national news outlets such as NPR, Vice News, Scientific American, and he regularly speaks at national and international scientific meetings on the topic of AI in healthcare.
Dr. Lungren is also a top rated instructor leading AI in Healthcare courses designed especially for learners with non-technical backgrounds:
Stanford/Coursera: https://www.coursera.org/learn/fundamental-machine-learning-healthcare
LinkedIn Learning: https://www.linkedin.com/learning/an-introduction-to-how-generative-ai-will-transform-healthcare -
Katharine (Kate) Maher
Professor of Earth System Science, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Earth and Planetary Sciences
Current Research and Scholarly InterestsHydrology, reactive transport modeling and environmental geochemistry
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Christopher Manning
Thomas M. Siebel Professor of Machine Learning, Professor of Linguistics, of Computer Science and Senior Fellow at the Stanford Institute for Human-Centered AI
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.
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David J. Maron
C. F. Rehnborg Professor and Professor of Medicine (Stanford Prevention Research Center)
Current Research and Scholarly InterestsDr. Maron is the Co-Chair and Principal Investigator of the ISCHEMIA trial, and Co-Chair of the ISCHEMIA-CKD trial. These large, international, NIH-funded studies will determine whether an initial invasive strategy of cardiac catheterization and revascularization plus optimal medical therapy will reduce cardiovascular events in patients with and without chronic kidney disease and at least moderate ischemia compared to an initial conservative strategy of optimal medical therapy alone.
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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.
