Recent coverage of my research in Science.
- “Explaining Algorithmic Decisions” at TTI/Vanguard. Washington, D.C.
- “The Perils and Promise of Predictive Analytics in Law” at the Stanford Center for Legal Informatics in Stanford, CA.
- “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 Institute for Operations Research and the Management Sciences Annual Meeting.
- “Machine Learning and Legal Prediction” at Fin Legal Tech Conference, Illinois Tech - Chicago Kent College of Law.
- “Predicting and Understanding Law with Machine Learning.” Data Science D.C. at George Washington University, Washington D.C.
- “Distributed Representations of Institutions and Their Policy Text” at International Conference on Computational Social Science, Evanston, IL.
- “Modeling Text for Legal Prediction and Analysis” at Gruter Institute for Law & Behavioral Research Annual Conference, Lake Tahoe, CA.
- “Natural Language Processing for Large Legal Databases” at the Workshop on Frontiers of Artificial Intelligence and the Law.
Open-source software packages:
- 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