|Nicolas Heess is a Research Scientist at DeepMind, London. He is interested in questions related to artificial intelligence and machine learning, perception, motor control, and robotics. One of his long-term goals is to develop algorithms and architectures that enable embodied agents to learn to intelligently reason about and interact with their physical environment and other agents. He has worked on the theory and applications of reinforcement learning and control, unsupervised learning, probabilistic models, and inference. His current research focuses on the application of these methods at the intersection of perception and control with a special interest in the acquisition, representation and adaptation of sensorimotor skills. Prior to joining DeepMind Nicolas was a postdoctoral researcher at the Gatsby Unit (UCL) working with Yee Whye Teh and David Silver. He did his PhD under the supervision of Chris Williams at the University of Edinburgh and also paid several extended visits to Microsoft Research (Cambridge, UK) where he worked with John Winn and others.