Institute for Human-Centered Artificial Intelligence (HAI)


Showing 1-19 of 19 Results

  • Monica Lam

    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

    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.

  • James Landay

    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.

  • Curtis Langlotz

    Curtis Langlotz

    Professor of Radiology (Thoracic Imaging), of Medicine (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.

  • Victor R. Lee

    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

    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

  • Jure Leskovec

    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

    Margaret Levi

    Professor of Political Science, Senior Fellow at the Freeman Spogli Institute for International Studies and at the Woods Institute for the Environment

    BioMargaret Levi is 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), Senior Fellow of the Woods Institute, and co-director of Ethics, Society and Technology, 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.

  • Ron Li

    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

    Percy Liang

    Associate Professor of Computer Science, Senior Fellow at the Stanford Institute for HAI, 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.

  • C. Karen Liu

    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.

  • Matthew Lungren

    Matthew Lungren

    Adjunct Professor, Biomedical Data Science

    BioDr. Lungren is Chief Data Science 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 a part-time clinical practice at UCSF while also continuing his 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 150 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 on Coursera where his AI in Healthcare course designed especially for learners with non-technical backgrounds has been completed by more than 20k students around the world - enrollment is open now: https://www.coursera.org/learn/fundamental-machine-learning-healthcare