I am currently a Data Insights Engineer at Flatiron Health, using machine learning to extract understanding from natural-language medical records. Before that, I received my PhD in Cognitive Psychology from New York University, where I worked in the Computation & Cognition Lab with Todd Gureckis. While there, I investigated how people learn and make decisions over time, with a particular focus on how people decide when to explore uncertain alternatives and the biases that can result from under-exploration. This research combined threads from the psychology literature on decision making and categorization with ideas from machine learning on forward-looking reinforcement learning and the fundamental limits to learning algorithms. Besides my primary doctoral research, I worked on a range of other fun projects, from combining psychological insights with gradient boosted decision trees to predict second language learning to using dynamic topic modeling to track the evolution of cognitive science. I was also one of the main developers of the psiTurk platform [github repository] for conducting replicable behavioral research online.
Between graduate school and Flatiron, I worked as a fellow at the University of Chicago Data Science for Social Good program based in Lisbon, Portugal. My team partnered with the Croatian Institute of Public Health to predict MMR vaccination refusal.