Institute for Human-Centered Artificial Intelligence (HAI)
Showing 1-13 of 13 Results
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Jennifer Pan
Sir Robert Ho Tung Professor of Chinese Studies, Professor of Communication, Senior Fellow at the Freeman Spogli Institute for International Studies and Professor, by courtesy, of Political Science and of Sociology
BioJennifer Pan is a political scientist whose research focuses on political communication, digital media, and authoritarian politics. She is the Sir Robert Ho Tung Professor of Chinese Studies, Professor of Communication and (by courtesy) Political Science and Sociology, and a Senior Fellow at the Freeman Spogli Institute.
Dr. Pan's research uses experimental and computational methods with large-scale datasets on political activity to answer questions about the role of digital media in politics, including how political censorship, propaganda, and information manipulation work in the digital age and how preferences and behaviors are shaped as a result. Her work has appeared in peer-reviewed publications such as the American Political Science Review, American Journal of Political Science, Journal of Politics, Science, and Nature.
She graduated from Princeton University, summa cum laude, and received her Ph.D. from Harvard University’s Department of Government. -
Vanessa Parli
Managing Director of Programs and External Engagement, Institute for Human-Centered Artificial Intelligence (HAI)
BioAs Managing Director, Programs and External Engagement at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), I lead initiatives that foster interdisciplinary collaboration and connect academic research with real-world impact. My work includes managing HAI’s industry research partnerships, executive education, policy engagement and the AI Index, creating opportunities for leaders from diverse backgrounds to engage with cutting-edge AI research, its applications, and its potential for positive social impact.
Before joining Stanford, I worked in management consulting, applying statistics, machine learning, and data science to advise government agencies, biotech firms, and nonprofit organizations. My work centered on making complex methods accessible to decision makers, ensuring technical rigor translated into actionable strategies.
I hold an MS in Engineering Management and Computational Mathematics from Johns Hopkins University and a BA in Industrial Engineering from Arizona State University. I am passionate about turning bold ideas into impact, and am recognized for my collaborative, process-driven approach to problem-solving. -
Marco Pavone
Associate Professor of Aeronautics and Astronautics, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Electrical Engineering & of Computer Science
BioDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he directs the Autonomous Systems Laboratory and the Center for Automotive Research at Stanford. He is also a Distinguished Research Scientist at NVIDIA where he leads autonomous vehicle research. Before joining Stanford, he was a Research Technologist within the Robotics Section at the NASA Jet Propulsion Laboratory. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He is a recipient of a number of awards, including a Presidential Early Career Award for Scientists and Engineers from President Barack Obama, an Office of Naval Research Young Investigator Award, a National Science Foundation Early Career (CAREER) Award, a NASA Early Career Faculty Award, and an Early-Career Spotlight Award from the Robotics Science and Systems Foundation. He was identified by the American Society for Engineering Education (ASEE) as one of America's 20 most highly promising investigators under the age of 40. His work has been recognized with best paper nominations or awards at a number of venues, including the European Conference on Computer Vision, the IEEE International Conference on Robotics and Automation, the European Control Conference, the IEEE International Conference on Intelligent Transportation Systems, the Field and Service Robotics Conference, the Robotics: Science and Systems Conference, and the INFORMS Annual Meeting.
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Roy Pea
Director, H-STAR, David Jacks Professor of Education and Professor, by courtesy, of Computer Science
Current Research and Scholarly Interestslearning sciences focus on advancing theories, research, tools and social practices of technology-enhanced learning of complex domains
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Alex P Pentland
Center Fellow at the Stanford Institute for Human-Centered AI
BioAlex “Sandy” Pentland is HAI Center Fellow and faculty lead for digital society at Stanford HAI and Digital Economy Lab, He is Toshiba Professor at MIT, member of US National Academies, Advisor to Abu Dhabi Investment Authority Lab, and formerly advisory board member at UN Secretary General’s office, Google, ATT, Telefonica, and elsewhere. Spin-off companies and open source systems from his lab manage authentication of most digital transactions in the world, media for roughly 1B people in far east, and health resources for roughly 0.5B people in the indopacific. His current focus is on problems and opportunities in using AI to improve our social institutions.
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VJ Periyakoil, Professor of Medicine
Professor of Medicine (Primary Care and Population Health)
Current Research and Scholarly InterestsMy lab is focused on longevity and healthy aging research.
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Kilian M Pohl
Professor (Research) of Psychiatry and Behavioral Sciences (Major Labs and Incubator) and, by courtesy, of Electrical Engineering
Current Research and Scholarly InterestsThe foundation of the laboratory is computational science aimed at identifying biomedical phenotypes improving the mechanistic understanding, diagnosis, and treatment of neuropsychiatric disorders. The biomedical phenotypes are discovered by unbiased, machine learning-based searches across biological, neuroimaging, and neuropsychological data. This data-driven discovery currently supports the adolescent brain research of the NIH-funded National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA). The laboratory also investigates brain patterns specific to alcohol use disorder, depression, and the human immunodeficiency virus (HIV) across the adult age range, and have advanced the understanding of a variety of brain diseases including schizophrenia, Alzheimer’s disease, glioma, and aging.
