Department of Statistics and the College
Nikolaos Ignatiadis is a statistician with formal training in mathematics, molecular biology, and computation. His research is inspired by new modeling and inference opportunities made possible through the wealth of modern data. In his research, he develops practical and theoretically justified statistical methods, accompanied by robust software implementations. His methodological interests encompass empirical Bayes analysis, causal inference, multiple testing, and statistics in the presence of contextual side information.
His research has been published in Biometrika, Journal of the American Statistical Association (Theory and Methods), The Journal of the Royal Statistical Society Series B (Statistical Methodology), and Nature Methods.
Ignatiadis earned a BSc with distinction in mathematics, a BSc in molecular biotechnology, and an MSc in scientific computing, all from Heidelberg University. He then completed an MS and a PhD in statistics at Stanford University. Most recently, he was a postdoctoral research fellow in the Department of Statistics at Columbia University.