I’m a Ph.D. student in the Princeton Psychology Department, where I study human decision-making both theoretically and experimentally. So far, I’ve focused on understanding how we make decisions about the future (time preferences) and how we deal with uncertainty (risk/ambiguity preferences). My long-term hope is to combine the clean experimental design and descriptively accurate models that psychologists are known for with the rigorous formal theory-building that economists prefer.
My work on time preferences is supervised by my primary advisor, Jon Cohen, and is part of a longstanding collaboration with two economists: David Laibson at Harvard University and Keith Ericson at Boston University. My recent work on ambiguity preferences is part of a collaborative effort that includes Bob Wilson, Carlos Diuk, Elliot Ludwig and Andra Geana.
In addition to my work on decision-making, I’ve collaborated with Dan Osherson, Nick Turk-Browne, Jiaying Zhao and Ray Lee on higher-level vision. With Dave Blei, I’ve applied statistical text analysis to some problems in the social sciences.
Outside of academia, I’ve been heavily involved in the data science movement, which has pushed for an open source software approach to data analysis. Along with the political scientist Drew Conway, I’m the author of a book published by O’Reilly Media entitled “Machine Learning for Hackers”, which is meant to introduce experienced programmers to the machine learning toolkit. I’m also working with Mark Hansen on a book for laypeople about exploratory data analysis.
Prior to entering academia, I played in a variety of rock bands, including Kids Icarus, Marigold and Dellamorte Dellamore. I also wrote a short album of acoustic songs with Aileen Quinn. Lately I’ve started playing music again and hope to have new work to share in the near future.
I’m also an avid rock climber, an hobbyist photographer and a vegetarian.