My research focuses on methods for principled, sample-efficient optimization including Bayesian optimization and transfer learning. I am a co-creator of BoTorch---an open source library for Bayesian optimization research. I am particularly interested in practical methods for principled exploration (using probablistic models) that are robust across applied problems and depend on few, if any, hyperparameters.