You can read my research statement here to learn more about my research interests and approach.

Research

Published Papers

An Introduction to Conformal Inference for Economists

With Mark E. Schaffer (2025). Invited paper for the Eighth International Econometric Conference of Vietnam, 'Artificial Intelligence and Machine Learning in Econometrics', 2025

Provides an accessible overview of conformal inference methods and their relevance for econometric applications.

machine learning conformal inference econometrics

Working Papers

Testing for improvements in algorithmic decision making

Developing a framework for intelligent resource allocation across cloud and edge infrastructure to optimize performance and energy consumption.

Algorithmic Fairness Empirical Welfare Maximization

Ensembling prediction sets with coverage guarantees via concentration inequalities

This paper introduces a novel method for ensembling conformal prediction sets from multiple models via concentration inequalities, ensuring guaranteed overall coverage.

conformal prediction ensemble methods concentration inequalities

Adaptive ensembling of prediction sets in online time series forecasting

In this paper, I develop an online, adaptive ensemble conformal prediction algorithm for time series forecasting. The method dynamically updates model coverage parameters and ensemble weights to maintain target coverage guarantees while adapting to potential distribution shifts.

time series forecasting adaptive ensembling online learning

Leaving the Church. A Note on the 1843 Disruption of the Church of Scotland

With John W. Sawkins (2024)

economic history institutional change