I am a staff research scientist working in statistical machine learning and artificial intelligence at DeepMind, London, where we work towards the goal of developing intelligent and general-purpose learning systems.
I am most interested in research that combines multiple scientific disciplines and views of computational and machine learning problems. Much of my current focus is on the interface between probabilistic reasoning, deep learning and reinforcement learning, and how the computational solutions that emerge in this space can be used for systems and agent-based decision-making. I love exploring and writing about the connections between different computational paradigms and maintain a blog at blog.shakirm.com.
Before moving to London, I held a Junior Research Fellowship from the Canadian Institute for Advanced Research (CIFAR) as part of the programme on Neural Computation and Adaptive Perception. I was based in Vancouver at the University of British Columbia in the Laboratory for Computational Intelligence (LCI) with Nando de Freitas.