Institute for Human-Centered Artificial Intelligence (HAI)


Showing 1-7 of 7 Results

  • Christine Raval

    Christine Raval

    Research Associate, Institute for Human-Centered Artificial Intelligence (HAI)

    BioChristine is a member of the research team at the Stanford Institute for Human-Centered AI (HAI). She manages the HAI grant programs, student affinity initiative, and the operations of AI100, a 100-year effort to study and anticipate how the effects of AI will ripple through every aspect of how people work, live and play. Prior to joining Stanford, Christine worked on the digital learning team at the University of Nebraska at Omaha and as a case manager for newly arrived refugees in Omaha. Christine graduated with a Master of Public Administration from the University of Nebraska at Omaha and a BA in Justice and Society from Creighton University.

  • Christopher Re

    Christopher Re

    Associate Professor of Computer Science

    Current Research and Scholarly InterestsAlgorithms, systems, and theory for the next generation of data processing and data analytics systems.

  • Rob Reich

    Rob Reich

    McGregor-Girand Professor of Social Ethics of Science and Technology, Senior Fellow at the Stanford Institute for HAI. Professor, by courtesy, of Education, of Philosophy and Senior Fellow, by courtesy, at FSI
    On Leave from 10/01/2023 To 06/30/2024

    BioRob Reich is professor of political science and, by courtesy, professor of philosophy and at the Graduate School of Education. He is a co-director of the Center on Philanthropy and Civil Society (publisher of the Stanford Social Innovation Review), and associate director of the Institute for Human-Centered Artificial Intelligence. He was faculty director at the Center for Ethics in Society for eight years, and he continues to lead its ethics and technology initiatives.

    His scholarship in political theory engages with the work of social scientists and engineers. His newest work is on ethics and AI. His most recent books are System Error: Where Big Tech Went Wrong and How We Can Reboot (with Mehran Sahami and Jeremy M. Weinstein, HarperCollins 2021) and Digital Technology and Democratic Theory (edited with Lucy Bernholz and Hélène Landemore, University of Chicago Press 2021). He has also written widely about philanthropy, including Just Giving: Why Philanthropy is Failing Democracy and How It Can Do Better (Princeton University Press, 2018) and Philanthropy in Democratic Societies: History, Institutions, Values (edited with Chiara Cordelli and Lucy Bernholz, University of Chicago Press, 2016). His early work is focused on democracy and education, including Bridging Liberalism and Multiculturalism in American Education (University of Chicago Press, 2002) and Education, Justice, and Democracy (edited with Danielle Allen, University of Chicago Press, 2013). He has written for the New York Times, Washington Post, Wired, The Guardian, and the Stanford Social Innovation Review.

    Rob is the recipient of multiple teaching awards, including the Walter J. Gores award, Stanford’s highest honor for teaching. He was a sixth grade teacher at Rusk Elementary School in Houston, Texas before attending graduate school. He is a board member of the magazine Boston Review, of Giving Tuesday, and at the Spencer Foundation.

  • Thomas Robinson

    Thomas Robinson

    The Irving Schulman, M.D. Professor of Child Health, Professor of Medicine (Stanford Prevention Research Center) and, by courtesy, of Epidemiology and Population Health

    Current Research and Scholarly InterestsDr. Robinson originated the solution-oriented research paradigm and directs the Stanford Solutions Science Lab. He is known for his pioneering obesity prevention and treatment research, including the concept of stealth interventions. His research applies social cognitive models of behavior change to behavioral, social, environmental and policy interventions for children and families in real world settings, making the results relevant for informing clinical and public health practice and policy.

  • Fatima Rodriguez

    Fatima Rodriguez

    Associate Professor of Medicine (Cardiovascular Medicine)

    BioFatima Rodriguez, MD, MPH is an Associate Professor in Cardiovascular Medicine and (by courtesy) the Stanford Prevention Research Center. Dr. Rodriguez earned her medical degree from Harvard Medical School and her MPH from the Harvard School of Public Health. She then completed internal medicine residency at Brigham and Women’s Hospital and fellowship in cardiovascular medicine at Stanford University. She currently serves as the Section Chief of Preventive Cardiology. Dr. Rodriguez specializes in cardiovascular disease prevention, inherited lipid disorders, and cardiovascular risk assessment in high-risk populations.

    Dr. Rodriguez’s research includes a range of topics around racial, ethnic, and gender disparities in cardiovascular disease prevention, developing novel interventions to address disparities, and opportunistic screening of coronary artery disease.

  • Daniel Rubin

    Daniel Rubin

    Professor of Biomedical Data Science, of Radiology (Integrative Biomedical Imaging Informatics at Stanford), of Medicine (Biomedical Informatics Research) and, by courtesy, of Ophthalmology

    Current Research and Scholarly InterestsMy research interest is imaging informatics--ways computers can work with images to leverage their rich information content and to help physicians use images to guide personalized care. Work in our lab thus lies at the intersection of biomedical informatics and imaging science.

  • Ahmad Rushdi

    Ahmad Rushdi

    Academic Prog Prof 3, Institute for Human-Centered Artificial Intelligence (HAI)

    BioAhmad A. Rushdi is a Sr. Research Manager at the Stanford Institute for Human-Centered AI (HAI). He works with the diverse machine learning, deep learning, and artificial intelligence communities across Stanford and the corporate world, in order to envision, build, and maintain new bridges around cutting-edge research that would create useful and trusted systems for a variety of AI applications.

    Dr. Rushdi's research interests include statistical signal processing and uncertainty quantification methods applied to machine learning models trained on time-series and real/synthetic image datasets. His publications span system design, communications, genomics, meshing, and national security applications.

    Prior to joining Stanford, Ahmad was a research scientist at the Center for Computing Research of Sandia National Laboratories, an R&D manager of data science at Northrop Grumman Corporation, a research fellow at the Department of Electrical and Computer Engineering of UC Davis and the Computational Visualization Center under Oden Institute for Computational Engineering and Sciences at UT Austin, and an R&D engineer at Cisco Systems.

    Ahmad holds a PhD in Electrical and Computer Engineering from the University of California, Davis, and MSc/BSc degrees in Electrical Engineering from Cairo University.