Fall 2025 Academic Job Market

Easton is currently on the fall 2025 academic job market. He is specifically interested in an appointment within quantitative groups in business schools, such as quantitative marketing or business analytics.

Easton’s Academic/Professional Timeline

Research Background

Easton’s academic background is statistics. He is a rising 4th-year PhD student in the Department of Statistics at the University of Michigan. His advisors are Fred Feinberg and Walter Dempsey. Easton’s research focuses on causal inference, especially in dynamic settings in which individuals receive multiple treatments over time. Past projects include:

• Data integration methods for micro-randomized trials (arXiv; revise and resubmit at Biometrics)
• A Robust Mixed-Effects Bandit Algorithm for Assessing Mobile Health Interventions (arXiv; under review at ML conference)

In addition to the completed projects above, Easton has several projects that he expects to submit for publication within the next 12 months:

• Bayesian randomization inference: A framework for robust Bayesian causal inference via randomization distributions (working paper; planning to submit to Journal of the Royal Statistical Society, Series B fall 2024)
• Computationally efficient models for count data with varying levels of dispersion (working paper; planning to submit to Journal of Business and Economic Statistics fall 2024)
• Likelihood-free Bayesian inference of regression models via permutation distributions (expected summer 2025)