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United States Ziad Obermeyer stands as a leading researcher and practitioner at the intersection of machine learning, medicine, and health policy.
Dandelion Health is a startup co-founded by Ziad Obermeyer that uses 10 million patient records to reduce bias in healthcare AI and cracks the clinical data bottleneck limiting AI in healthcare. It launches pilots to evaluate AI performance and potential bias.
A new collaboration designed as an innovation and learning network to address challenges of new algorithms for all use cases in a rapidly evolving healthcare landscape.
Ziad Obermeyer co-founded Nightingale, which takes de-identified data sets out of the healthcare system and makes them available to researchers.
On The Dose podcast, Ziad Obermeyer discussed the potential of AI to inform health outcomes — for better and for worse, addressing how AI can improve health without perpetuating bias.
Ziad Obermeyer discussed how machine learning and AI are being used for medical research and diagnoses, and helping doctors make better decisions with data.
Obermeyer et al. published a pivotal paper dissecting racial bias in a widely used algorithm, finding that Black patients assigned the same risk level by the algorithm were sicker than White patients.
Ziad Obermeyer has been featured for pioneering healthcare transformation through machine learning, focusing on the intersection of machine learning with health since 2017.
Ziad Obermeyer was featured on the “Not Otherwise Specified” Podcast – Medicine Machines, where he discussed his work in applying machine learning to population health.
Ziad Obermeyer testified before the U.S. Congress on how artificial intelligence can assist doctors and others in the healthcare system to make better decisions, aiming to improve health and reduce disparities.
Mentioned as a funder on a slide related to the Ethics of Building + Implementing Predictive Analytics, indicating support for research in this area.
Mentioned as a funder on a slide related to the Ethics of Building + Implementing Predictive Analytics, indicating support for research in this area.
Ziad Obermeyer is the Blue Cross of California Distinguished Associate Professor of Health Policy and Management at the UC Berkeley School of Public Health. His research focuses on the application of machine learning in medicine and health policy, aiming to improve healthcare outcomes and address systemic biases. Before his role at UC Berkeley, Obermeyer served as an Assistant Professor at Harvard Medical School. During his tenure at Harvard, he was recognized with the Early Independence Award, a prestigious award from the National Institutes of Health, acknowledging his contributions as a junior scientist.
Obermeyer maintains an active medical practice, working as an emergency medicine physician in underserved areas in the United States. Prior to his career in medicine, he worked as a consultant for McKinsey & Co., where he advised pharmaceutical and global health clients. His consulting experience spanned multiple international locations, including New Jersey, Geneva, and Tokyo. His foundational education includes an MD from Harvard Medical School, an MPhil from Cambridge, and a BA from Harvard College.
Throughout his career, Ziad Obermeyer has achieved significant milestones in the field of AI and healthcare. In September 2023, he was named one of TIME’s top 100 leaders in artificial intelligence. He was also recognized as an emerging leader in health research by the National Academy of Medicine in May 2020. Obermeyer actively contributes to academic discourse, teaching courses such as “Artificial Intelligence for Medicine and Health Policy” and “Data Science in Health Policy” at UC Berkeley. His work includes co-founding Dandelion Health, a company focused on leveraging clinical data to address biases and improve AI performance in healthcare.
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