Matt Taddy is Associate Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. His research is focused on methodology in statistics, econometrics, and machine learning, and applications in business, social science, and engineering. Taddy works on building robust solutions for large-scale data analysis problems and on quantifying uncertainty about the output of these algorithms. He has collaborated with small start-ups and with large research agencies, including NASA Ames, Lawrence Livermore, Sandia, and Los Alamos National Laboratories, and he is a research fellow at eBay. He also created and teaches the Booth Big Data course.
Taddy earned his PhD in Applied Math and Statistics in 2008 from the University of California, Santa Cruz, as well as a BA in Philosophy and Mathematics and an MSc in Mathematical Statistics from McGill University. He joined the Chicago Booth faculty in 2008.
2015 - 2016 Course Schedule