Hi, I'm Danijar! My goal is to develop autonomous artificial intelligence that makes decisions given only limited human instruction.

I'm a PhD candidate at the University of Toronto with Jimmy Ba, a visiting student at UC Berkeley with Pieter Abbeel, and an intern at DeepMind. Previously, I interned at Google Brain for 6 years. I completed my MRes at UCL and the Gatsby Unit with Tim Lillicrap and Karl Friston. My work is supported by Canada's Vanier Scholarship.

Contact: mail AT danijar.com


My research aims at discovering the computational principles of human thinking and replicating them to build useful artificial intelligence. I approach this challenge by designing unsupervised algorithms that learn through interaction with complex environments, going beyond task-specific agents that are inherently narrow in their abilities.

The key questions I’m currently focusing on are:

This talk gives a good technical overview of my research.

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Highlighted Work

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Short Biography

Danijar Hafner is a visiting student at the University California, Berkeley with Pieter Abbeel and a PhD candidate in artificial intelligence at the University of Toronto with Jimmy Ba. He is also a student researcher at Google Research and the Vector Institute. Danijar’s research aims to build intelligent machines based on the computational principles of the brain. Towards this goal, he focuses on scaling up embodied artificial intelligence through general world models, unsupervised objectives, and deep reinforcement learning. Danijar completed his MRes in Computational Statistics and Machine Learning at UCL and the Gatsby Unit with Tim Lillicrap and Karl Friston. His work is supported by Canada’s Vanier Scholarship.

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