I am a PhD student at the University of Toronto, advised by Jimmy Ba and Geoffrey Hinton. I am also a student researcher at Google Brain and the Vector Institute. I finished my MRes in CSML at University College London, advised by Tim Lillicrap and Karl Friston.
My goal is to build intelligent machines based on concepts of the human brain, and evaluate them in complex simulations. Currently, I’m focusing on agents that learn without rewards, reinforcement learning with world models, and unsupervised learning.
If you have any questions, feel free to contact me at [email protected].
2019-03-01 Accepting student researchers at the Vector Institute.
2018-11-28 We organize the ICLR 2019 workshop on task-agnostic RL.
2018-02-16 Guest lecture at Stanford CS 20 on Variational Inference in TF.
Please see my Scholar profile for a full list including article links.
Danijar Hafner is a PhD student at the University of Toronto advised by Jimmy Ba and Geoffrey Hinton. He is also a student researcher at Google Brain and the Vector Institute. His research focuses on artificial intelligence, specifically reinforcement learning with world models and intrinsic objectives for agents that learn without rewards. Danijar obtained his MRes at the University College London and the Gatsby Unit under the supervision of Tim Lillicrap and Karl Friston. Danijar co-authored the book “TensorFlow for Machine Intelligence” and advises Stanford’s course “TensorFlow for Deep Learning Research”. He completed his bachelor’s thesis on deep reinforcement learning for the video game Doom at the Hasso Plattner Institute, Germany.