Her primary research goal is to develop learning algorithms for autonomous agents learning on streams of data. To achieve this goal, her research focus is on developing practical algorithms for reinforcement learning and representation learning, including parameter-free, sample-efficient learning methods for policy evaluation and control in reinforcement learning and principled optimization approaches for sparse coding, kernel representations and neural networks.