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We are co-hosting the Distinguished Visitor Lecture organised by QUT and IFE

Deep Reinforcement Learning in the Real World
Raia Hadsell (Google DeepMind)

When: Thursday 10 August, 3:30pm – 4:30pm 
Where: Room P-419, Level 4, P Block, QUT Gardens Point (map)

Please register if you would like to attend


Deep reinforcement learning has rapidly grown as a research field with far-reaching potential for artificial intelligence. Large sets of ATARI games have been used as the main benchmark domain for many fundamental developments. As the field matures, it is important to develop more sophisticated learning systems with the aim of solving more complex tasks. This presentation will describe some recent research from DeepMind that allows end-to-end learning in challenging environments with real-world variability and complex task structure.

Raia Hadsell, a senior research scientist at DeepMind, has worked on deep learning and robotics problems for over 10 years. Her early research developed the notion of manifold learning using Siamese networks, which has been used extensively for invariant feature learning. After completing a PhD with Yann LeCun, which featured a self-supervised deep learning vision system for a mobile robot, her research continued at Carnegie Mellon’s Robotics Institute and SRI International, and in early 2014 she joined DeepMind in London to study artificial general intelligence. Her current research focuses on the challenge of continual learning for AI agents and robots. For further information, view Raia’s website here:


August 10


03:30 pm - 04:30 pm

Click to Register:

Brisbane Artificial Intelligence


QUT Gardens Point, P Block, Level 4 419 (GP-P419)

QUT Gardens Point , Brisbane

Brisbane, AU