About me
Ben Seiler is a postdoctoral research fellow in the department of Epidemiology and Population Health at the Stanford School of Medicine. He specializes in developing and deploying interpretable statistical learning methods. As part of the Stanford Human Trafficking Data Lab, Ben currently works on quantitative approaches to issues of labor trafficking and child labor in Brazil. He holds a PhD in Statistics from Stanford University where his research was focused on feature importance and algorithmic fairness in machine learning. Before Stanford, he earned a BA in physics, economics, and mathematics from Williams College. After completing his BA, he worked as a foreign exchange derivatives trader at Goldman Sachs from 2013 to 2018.
