Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)
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Eran Segal is Dean of the Biological and Life Sciences Division and Professor of Computational Biology at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). He holds a B.Sc. in Computer Science summa cum laude from Tel-Aviv University and a Ph.D. in Computer Science with a minor in genetics from Stanford University. Prior to joining MBZUAI, he served as Professor of Computer Science at the Weizmann Institute of Science and held an independent research position at Rockefeller University.
Professor Segal’s research focuses on developing multi-modal AI models for personalized medicine based on big data from human cohorts, including microbiome, genetics, nutrition, and lifestyle data. He heads the Human Phenotype Project, a large-scale prospective longitudinal cohort and biobank with more than 10,000 participants that his lab established to identify novel molecular markers and develop prediction models for disease onset and progression. Prior to joining MBZUAI, he published more than 200 peer-reviewed publications that have been cited more than 60,000 times. He received several awards and honors, including the Overton Prize from the International Society for Computational Biology in 2008, the Michael Bruno Prize in 2015, election as an EMBO Member in 2015, European Research Council grants, and membership in the Young Israeli Academy of Science. During the COVID-19 pandemic, he developed models for analyzing pandemic dynamics and served as a senior advisor to the government of Israel. He was elected as a member of the Scientific Advisory Committee of the National AI Initiative of Israel in 2023.
Explore MBZUAI's Human Phenotype Project, a Nature Medicine study mapping health evolution and early disease onset via AI and multimodal data from 28,000 participants.
Explore MBZUAI's Human Phenotype Project and the groundbreaking GluFormer AI model published in Nature, revolutionizing diabetes and cardiovascular risk prediction using deep phenotyping data.
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