Hadi Elzayn is a Postdoctoral Fellow at RegLab, where he focuses on applying machine learning algorithms to close the tax gap. He holds a PhD in Applied Mathematics and Computational Science at the University of Pennsylvania, where he was advised by Michael Kearns. In addition to fundamental questions at the intersection of computer science and economics, he is interested in how algorithms in general, and machine learning in particular, can exacerbate or improve societal concerns around fairness, privacy, and markets. He has interned at Facebook, Microsoft Research, and the Federal Reserve Bank of Philadelphia, and worked for several years at TGG Group, a Chicago-based consulting firm applying econometrics and behavioral economics to solve problems for business, non-profits, and government. He received his B.A. in Mathematics and Economics from Columbia University.