My research aims to develop scalable methods to build broadly intelligent agents that require minimal human supervision. I am excited by problems involving interesting distributional shifts in both reinforcement learning and supervised learning and work to develop models that can generalize or adapt to changing environments. I am supported by an NSF Graduate Research Fellowship.