Patrick Vossler

Patrick Vossler

Postdoctoral Researcher

Stanford Law School

Biography

I am a postdoctoral researcher at the Regulation, Evaluation, and Governance Lab at Stanford Law School where I am hosted by Prof. Daniel E. Ho. I received my Ph.D. from the University of Southern California’s Marshall School of Business department of Data Sciences and Operations where I was advised by Prof. Yingying Fan and Prof. Jinchi Lv.

My research involves improving our theoretical understanding of commonly-used machine learning methods in high-dimensional settings and applying these methods to important real-world problems. My research at RegLab focuses on using machine learning methods to help better estimate the tax gap.

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Interests
  • Causal Inference
  • Nonparametric and semi-parametric statistics
  • Random Forests
Education
  • Ph.D. in Statistics, 2022

    University of Southern California

  • B.S. in Economics and Mathematics, 2017

    University of Southern California

Featured Publications

(2022). Asymptotic Properties of High-Dimensional Random Forests. The Annals of Statistics.

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(2022). Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors. Journal of the American Statistical Association.

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(2021). Dimension-Free Average Treatment Effect Inference with Deep Neural Networks.

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