Institute for Human-Centered Artificial Intelligence (HAI)
Showing 31-40 of 276 Results
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Erik Brynjolfsson
Jerry Yang and Akiko Yamazaki Professor, Senior Fellow at Stanford Institute for Human-Centered Artificial Intelligence, at SIEPR & Professor, by courtesy, of Economics & of Operations, Information & Technology & of Economics at the GSB
BioErik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Director of the Stanford Digital Economy Lab at HAI. He is also the Ralph Landau Senior Fellow at SIEPR, and a Professor, by courtesy, at the Stanford Graduate School of Business and at the Department of Economics. Prof. Brynjolfsson is a Research Associate at the National Bureau of Economic Research and co-author of six books, including The Second Machine Age. His research, teaching and speaking focus on the effects of digital technologies, including AI, on the economy and business.
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Jef Caers
Professor of Earth and Planetary Sciences and, by courtesy, of Geophysics
Current Research and Scholarly InterestsMy research focuses on assuring 100% renewable energy through development of geothermal energy and critical mineral supply, developing approaches from data acquisition to decision making under uncertainty and risk assessment.
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Danton Char
Associate Professor of Anesthesiology, Perioperative and Pain Medicine (Pediatric)
Current Research and Scholarly InterestsDr. Char's research is focused on identifying and addressing ethical concerns associated with the implementation of next generation technologies like whole genome sequencing and its attendant technologies like machine learning to bedside clinical care.
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Akshay Chaudhari
Assistant Professor (Research) of Radiology (Integrative Biomedical Imaging Informatics at Stanford) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsDr. Chaudhari is interested in the application of artificial intelligence techniques to all aspects of medical imaging, including automated schedule and reading prioritization, image reconstruction, quantitative analysis, and prediction of patient outcomes. His interests range from developing novel data-efficient machine learning algorithms to clinical deployment and validation of patient outcomes. He is also exploring combining imaging with clinical, natural language, and time series data.
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Jonathan H. Chen, MD, PhD
Assistant Professor of Medicine (Biomedical Informatics)
Current Research and Scholarly InterestsInformatics solutions ares the only credible approach to systematically address challenges of escalating complexity in healthcare. Tapping into real-world clinical data streams like electronic medical records will reveal the community's latent knowledge in a reproducible form. Delivering this back as clinical decision support will uniquely close the loop on a continuously learning health system.
