My research has spanned from general machine learning and data mining to privacy preserving data mining, text mining, semi-supervised learning, active learning, information retrieval, NLP, and knowledge management. Most of my work in the past few years has focused on developing and using machine learning & data mining approaches to solve large-scale problems in corporate, political, and non-profit areas.
My current interests lie at the intersection of Machine Learning/Data Mining, Public Policy, and Social Sciences. I'm interested in solving large-scale and high impact social problems using data driven and evidence based methods. A lot of government, civic, and non-profit organizations are realizing the value of better data and have been focusing on improving data collection and data standardization. My goal is to build on these efforts, and work with these organizations to use this data to help improve outcomes for these organizations. I'm also interested in approaches that allow these organizations to efficiently measure the impact of such interventions and programs in order to do better resource allocation and focus on efforts that lead to better outcomes.