Patrick Vossler is a postdoctoral scholar at Stanford University’s RegLab. He received his Ph.D. from the University of Southern California, where he was advised by Professors Jinchi Lv and Yingying Fan. Patrick’s 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. His research at RegLab focuses on using machine learning methods to help better estimate the tax gap.