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Nikolaos Ignatiadis is an Assistant Professor in the Department of Statistics and the College at the University of Chicago, with a research focus that spans both theoretical and applied areas of statistics. He has a strong academic background, having completed his Ph.D. in Statistics at Stanford University, where his thesis was awarded the Jerome H. Friedman dissertation award. Prior to his current role, he served as a postdoctoral research scientist in the Department of Statistics at Columbia University. His educational journey also includes a B.Sc. in Mathematics and Molecular Biotechnology, along with a Master’s degree in Scientific Computing from the University of Heidelberg in Germany. Ignatiadis's methodological interests lie in empirical Bayes analysis, causal inference, and multiple testing, particularly in contexts where side-information is present. His work emphasizes the development of practically justified statistical methods and robust software implementations that aid in the analysis of datasets generated by modern technologies. He is driven by a desire to innovate within statistical modeling and inference, exploring the opportunities presented by a wealth of contemporary data.
Department of Philosophy