Josephine Akosa is a Visiting Assistant Professor of IT, Analytics, and Operations in the Mendoza College of Business at the University of Notre Dame. Her research interest is in high-dimensional statistical inference. Rapid advancement in technology has allowed an accelerated increase in the amount of data collected in many research fields, thereby allowing for thousands of hypotheses to be tested with a relatively small number of experimental units. The problem here is that multiplicity adjustment must be made but traditional methods are designed in the realm of independent and normally distributed data with the dimension of the data being smaller than the sample size, when in fact these are not the characteristics of high-dimensional inferential problems. Professor Akosa focuses on developing powerful multiple comparison procedures for non-normally distributed data that incorporate small sample adaptations to estimation procedures of model parameters. She has also worked on projects involving imbalanced data modeling.