Nikos Ignatiadis
I am an assistant professor of Statistics and Data Science at the University of Chicago. Previously, I was a postdoctoral research scientist in the Department of Statistics at Columbia University. I received my Ph.D. in Stanford’s Statistics department in the summer of 2022, and my thesis was recognized with the Jerome H. Friedman dissertation award. Before that, I received degrees in Mathematics (B.Sc.), Molecular Biotechnology (B.Sc.), and Scientific Computing (M.Sc.) at the University of Heidelberg in Germany, where I was a researcher at the European Molecular Biology Laboratory.
As a statistician with formal training in mathematics, molecular biology, and computation, I seek to develop practical and theoretically justified statistical methods, accompanied by robust software implementations, for the analysis of datasets generated from modern technologies. My research is inspired by new modeling and inference opportunities made possible through the wealth of modern data. My methodological interests encompass empirical Bayes analysis, causal inference, multiple testing, and statistics in the presence of contextual side-information.