Institute for Human-Centered Artificial Intelligence (HAI)


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  • Daniel Yamins

    Daniel Yamins

    Assistant Professor of Psychology and of Computer Science

    Current Research and Scholarly InterestsOur lab's research lies at intersection of neuroscience, artificial intelligence, psychology and large-scale data analysis. It is founded on two mutually reinforcing hypotheses:

    H1. By studying how the brain solves computational challenges, we can learn to build better artificial intelligence algorithms.

    H2. Through improving artificial intelligence algorithms, we'll discover better models of how the brain works.

    We investigate these hypotheses using techniques from computational modeling and artificial intelligence, high-throughput neurophysiology, functional brain imaging, behavioral psychophysics, and large-scale data analysis.

  • Seema Yasmin

    Seema Yasmin

    Clinical Assistant Professor, Medicine - Primary Care and Population Health

    BioSeema Yasmin is an Emmy Award-winning journalist, poet, medical doctor and author. Yasmin served as an officer in the Epidemic Intelligence Service at the U.S. Centers for Disease Control and Prevention where she investigated disease outbreaks and was principal investigator on a number of CDC studies. Yasmin trained in journalism at the University of Toronto and in medicine at the University of Cambridge.

    Yasmin was a finalist for the Pulitzer Prize in breaking news in 2017 with a team from The Dallas Morning News for coverage of a mass shooting, and recipient of an Emmy for her reporting on neglected diseases. She received multiple grants from the Pulitzer Center on Crisis Reporting for coverage of gender based violence in India and the aftermath of the Ebola epidemic in West Africa. In 2017, Yasmin was a John S. Knight Fellow in Journalism at Stanford University investigating the spread of health misinformation and disinformation during public health crises. Previously she was a science correspondent at The Dallas Morning News, medical analyst for CNN, and professor of public health at the University of Texas at Dallas. She teaches crisis management and crisis communication at the UCLA Anderson School of Management as a Visiting Assistant Professor.

    She is the author of eight non-fiction, fiction, poetry and childrens books, including: What the Fact?! Finding the Truth in All the Noise (Simon and Schuster, 2022); Viral BS: Medical Myths and Why We Fall For Them (Johns Hopkins University Press, 2021); Muslim Women Are Everything: Stereotype-Shattering Stories of Courage, Inspiration and Adventure (HarperCollins, 2020); If God Is A Virus: Poems (Haymarket, 2021); Unbecoming: A Novel (Simon and Schuster, 2024); Djinnology: An Illuminated Compendium of Spirits and Stories from the Muslim World (Chronicle, 2024); and The ABCs of Queer History (Workman Books, 2024). Her writing appears in The New York Times, Rolling Stone, WIRED, Scientific American and other outlets.

    Yasmin’s unique expertise in epidemics and communications has been called upon by the Vatican, the Presidential Commission for the Study of Bioethical Issues, the Aspen Institute, the Skoll Foundation, the Biden White House, and others. She teaches a new paradigm for trust-building and evidence-based communication to leadership at the World Health Organization and CDC. In 2019, she was the inaugural director of the Stanford Health Communication Initiative.

    Her scholarly work focuses on the spread of scientific misinformation and disinformation, information equity, and the varied susceptibilities of different populations to false information about health and science. In 2020, she received a fellowship from the Emerson Collective for her work on inequitable access to health information. She teaches multimedia storytelling to medical students in the REACH program.

  • Serena Yeung-Levy

    Serena Yeung-Levy

    Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering

    BioDr. Serena Yeung-Levy is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. Her research focus is on developing artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. She has extensive expertise in deep learning and computer vision, and has developed computer vision algorithms for analyzing diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images.

    Dr. Yeung-Levy leads the Medical AI and Computer Vision Lab at Stanford. She is affiliated with the Stanford Artificial Intelligence Laboratory, the Clinical Excellence Research Center, and the Center for Artificial Intelligence in Medicine & Imaging. She is also a Chan Zuckerberg Biohub Investigator and has served on the NIH Advisory Committee to the Director Working Group on Artificial Intelligence.