Ziad Obermeyer is Associate Professor and Blue Cross of California Distinguished Professor at UC Berkeley, where he works at the intersection of machine learning and health. His research focuses on how machine learning can help doctors make better decisions (like whom to test for heart attack), and help researchers make new discoveries—by ‘seeing’ the world the way algorithms do (like finding new causes of pain that doctors miss, or linking individual body temperature set points to health outcomes). He also shown how widely-used algorithms affecting millions of patients automate and scale up racial bias. That work has impacted how many organizations build and use algorithms, and how lawmakers and regulators hold AI accountable.
He is 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. His papers appear in a wide range of journals (ICML, JAMA, Nature Medicine, the New England Journal of Medicine, the Quarterly Journal of Economics, Science), and win awards from professional societies in medicine and economics. His work on algorithmic bias is frequently cited in the public debate about artificial intelligence, and in federal and state regulatory guidance and investigations. He is a co-founder of Nightingale Open Science, a non-profit that makes massive new medical imaging datasets available for research, and Dandelion Health, a data platform for AI innovation. Previously, he was a consultant at McKinsey & Co., and an Assistant Professor at Harvard Medical School. He continues to practice emergency medicine in underserved communities.
Texas Covered is the largest event of its kind in Texas and brings together decision-makers from across the health care spectrum—from major health plans, providers and regulators, to legislators, journalists, academics and more.
