Danijar Hafner studies how artificial agents can learn models of their surroundings and use them to decide what to do. His work connects visual experience, prediction and action through a sequence of collaborative projects, including PlaNet, Dreamer and DayDreamer. These systems investigate planning and behaviour learning inside representations acquired from experience, with experiments ranging from simulated control and Minecraft to physical robots. Hafner completed doctoral research at the University of Toronto with Jimmy Ba, following studies at UCL and the Gatsby Unit and research experience at Berkeley and Google Brain. A former Staff Research Scientist at Google DeepMind, he was named among MIT Technology Review’s Innovators Under 35 in 2026. His trajectory offers a perspective on artificial intelligence centred on acting in an environment. The distinctions between learning a model, producing plausible predictions and achieving reliable behaviour remain essential to understanding both the significance and the limits of that work.
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