Welcome

I am a Ph.D. Candidate at the Vanderbilt University School of Engineering, a Research Fellow at Vanderbilt Law School’s Program on Law & Innovation, and a Co-Founder of PredictGov, Inc.

Interactively explore real-time predictions for the more than 9,000 bills currently under consideration in the U.S. Congress at PredictGov.

Presentations coming up this fall:

“Predicting Law with Machine Learning” at CodeX: Stanford Center for Legal Informatics.

“Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text” at the Conference on Empirical Methods in Natural Language Processing Workshop on Natural Language Processing and Computational Social Science.

“Text Modeling for Understanding and Predicting the Federal Government” at the 2016 Institute for Operations Research and the Management Sciences Annual Meeting.

“Betting and Belief: Prediction Markets and Attribution of Climate Change” at the 2016 Winter Simulation Conference.

Recent talks:

• “Predicting and Understanding Law with Machine Learning.” Data Science D.C. August Presentation at George Washington University, Washington D.C.
• “Distributed Representations of Institutions and Their Policy Text” June Presentation at International Conference on Computational Social Science, Evanston, IL.
• “Modeling Text for Legal Prediction and Analysis” May Presentation at Gruter Institute for Law & Behavioral Research Annual Conference, Lake Tahoe, CA.
• “Natural Language Processing for Large Legal Databases” April Presentation at the Workshop on Frontiers of Artificial Intelligence and the Law.
• “Predicting and Understanding Human Cooperation” March Presentation at Vanderbilt Microeconomics Seminar.
• “Forecasting Agricultural Productivity with Remote Sensing and Machine Learning”, March Presentation at Annual Meeting of National Science Foundation Water Sustainability and Climate Investigators, Arlington, VA.
• “Data-Driven Dynamic Decision Models” December Presentation at the 2015 Winter Simulation Conference, Huntington Beach, CA.
• “An R Package for Data-Driven Decision Modeling” October Presentation at Nashville R Users Group.

Websites for my open-source software pacakges:

• datafsm: Estimating Finite State Machine Models from Data
• forecastVeg: Python Scripts for Forecasting Vegetation Health
• predMarket: A Climate Prediction Market Simulation Model
• sa: Sensitivity Analysis for Complex Computational Models
• eat: Empirical Agent Training Software for Data-Driven Modeling
• agp: Agent Gentic Programming Software for Data-Driven Modeling