My research focuses on methods for principled, sample-efficient optimization including Bayesian optimization and transfer learning. I am particularly interested in practical methods for principled exploration (with probablistic models) that are are robust across applied problems and depend on few hyperparameters. Furthermore, I aim to democratize such methods by open sourcing reproducible code. Prior to joining Facebook, I worked with Finale Doshi-Velez at Harvard University on efficient and robust methods for transfer learning.

Exploration is a core part of my being, and it's a safe bet that you'll find me climbing, skiing, running, scuba diving, or scheming about how to get to the remote reaches of the world.