Publications & Work in Progress

My research spans privacy-preserving synthetic data generation, differential privacy, machine learning methods for social science, and election forecasting. Publications appear in venues including ICLR, PNAS, Harvard Data Science Review, and Political Analysis.

Forecasting Elections in Multi-Party Systems: A Bayesian Approach Combining Polls and Fundamentals

A dynamic Bayesian forecasting model for multi-party elections combining polls with fundamentals.

How Cross-Validation Can Go Wrong and What to Do About it

Demonstrating the severe consequences of problematic cross-validation usage in predictive modeling.

Zweitstimme.org: A structural-dynamic forecasting model for German federal elections

A structural-dynamic forecasting model combining polls with structural information for German elections.

A Partisan Treatment in a High Salience Election: Evidence from a Field Experiment in Germany

Field experiment evaluating the effectiveness of direct mail in a German high salience election.