Meta Research

I am a Research Scientist at Meta AI Research working on understanding the mechanisms underlying neural network computation and function, and using these insights to build machine learning systems more intelligently. In particular, I’ve worked on understanding the properties predictive of generalization, methods to compare representations across networks, the role of single units in computation, and on strategies to measure abstraction in neural network representations. Previously, I worked at DeepMind in London, and I earned my PhD in neurobiology at Harvard University, using machine learning to study the cortical dynamics underlying evidence accumulation for decision-making.