Speaker Profile
PMWC LUMINARY AWARD
Revealed racial bias in healthcare algorithms and helped define accountable clinical AI
M.D., Associate Professor, UC Berkeley
Biography
Ziad Obermeyer is Associate Professor and Blue Cross of California Distinguished Professor at UC Berkeley. His research uses machine learning to help doctors make better decisions, and help researchers make new discoveries—by ‘seeing’ the world the way algorithms do. His work on algorithmic racial bias has impacted how many organizations build and use algorithms, and how lawmakers and regulators hold AI accountable. He is a cofounder of Nightingale Open Science and Dandelion Health, a Chan Zuckerberg Biohub Investigator, a Faculty Research Fellow at the National Bureau of Economic Research, and was named an Emerging Leader by the National Academy of Medicine. Previously, he was Assistant Professor at Harvard Medical School, and continues to practice emergency medicine in underserved communities.
Talk
Bedside to bench: Reinventing medicine with AI
Machine learning, by engaging directly with images and waveforms, is starting to produce empirical discoveries that drive theoretical insights. Rebooting flow of ideas from ‘bedside to bench’—historically a key driver of progress—will give rise to major innovations in patient care and scientific discovery. It will also create a new science of medicine, powered by data.
Session Abstract – PMWC 2027 Silicon Valley
Davos of Precision Medicine
PMWC 2027 Program
January 27–29, 2027 · Santa Clara Convention Center
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