My current methods research interests include developing computational tools for dealing with the idiosyncrasies of online experiments, Bayesian experimental design and analysis, machine learning methods for text and image analysis with a special interest in Bayesian nonparametrics, hierarchical Bayesian modeling of spatial data and stochastic optimization methods. After graduating from Berkeley, I spent two awesome years in Cambridge as a Democracy Fellow at the Harvard Kennedy School of Government and am an affiliate of the Institute for Quantitative Social Science (IQSS). I also hold an AM in Statistics from the Harvard University Department of Statistics where Don Rubin was my adviser.
- Statistics of Causal Inference and Design of Experiments
- Bayesian Inference
- Machine Learning for Text and Image Analysis
- Computer Vision
- Scalable Stochastic Optimization
- Spatial Data Visualization and Analysis