Research Areas: Machine Learning, Data Science, Natural Language Processing, Computational Social Science, Forecasting, Information Systems, Public Policy, Regulation and Sustainability.
I’ve conducted research as part of the data science components of multiple National Science Foundation-funded projects and serve as a Co-PI on a grant to combine machine learning and econometric approaches to estimate causal effects.
I develop machine learning approaches to better understand and forecast. My computational work is directed toward law, policy and business applications, including the following recent publications:
- natural language processing of law and policy
- machine learning for predicting and understanding law-making
- computer simulations of climate prediction markets
- machine learning for forecasting drought globally with satellite data
- computational models predicting human cooperation
- machine learning for automatically estimating models of decision-making