I lead a collaborative project on “Inferring Human Preferences” with Andreas Stuhlmueller, Jessica Taylor and Noah Goodman. I’m working on techniques for learning about human beliefs, preferences and values from observing human behavior or interacting with humans. This draws on machine learning (e.g. inverse reinforcement learning and probabilistic programming), cognitive science, and analytic philosophy.
I was previously a PhD student at MIT. I worked on MIT’s Probabilistic Computing Project on tools and applications for Venture. I also worked on Bayesian cognitive science with Josh Tenenbaum. My dissertation was “Bayesian Computational Models for Inferring Preferences” (supervisor: Roger White).