Xuming He is chair of the IMS Committee to Select Editors. He introduces the incoming editors of three of the IMS journals:

We are pleased to introduce the editors-elect for several IMS flagship journals. Their three-year terms start January 1, 2022.

The Annals of Applied Probability aims to publish research of the highest quality reflecting the varied facets of contemporary applied probability. Kavita Ramanan and Qiman Shao have been appointed as Editors-elect of the journal. Kavita Ramanan is the Roland George Dwight Richardson University Professor of Applied Mathematics, Brown University. She works on probability theory, stochastic processes and their applications. Qiman Shao, Chair Professor of the Department of Statistics and Data Science, Southern University of Science and Technology, China, works on asymptotic approximations and large deviations in probability and statistics, as well as high-dimensional data analysis.

The Annals of Applied Statistics is a premier journal of applied statistics and aims to provide a timely and unified forum for all areas of applied statistics. Professor Ji Zhu from the Department of Statistics, University of Michigan, will succeed Karen Kafadar as Editor-in-Chief. His research interests include statistical learning, complex data analysis, and statistical modeling in a wide range of applications from health/medicine to finance and engineering. He will appoint several area-editors to assist him with the review process for the journal.

The Annals of Statistics aims to publish research papers of the highest quality reflecting the many facets of contemporary statistics. Enno Mammen and Lan Wang will succeed Richard Samworth and Ming Yuan as Editors. Enno Mammen is Professor of Mathematical Statistics at Heidelberg University, Germany. His research interests include asymptotic statistical decision theory, the bootstrap methods, and nonparametric models. Lan Wang is Professor of Statistics and Management Science at University of Miami. Her research interests cover optimal personalized decision recommendations, quantile regression, and high dimensional learning and inference.