Journal of the American Statistical Association (JASA) Applications and Case Studies and Coordinating Editor
Michael Stein, Rutgers University
Michael Stein is distinguished professor in the department of statistics at Rutgers University, which he joined in 2019 after spending many years on the faculty at The University of Chicago. His research interests include spatial statistics, spatio-temporal statistics, extremes, and statistical problems in the physical sciences, especially climatology.

Journal of Business & Economic Statistics (JBES) Co-Editors
Ivan Canay, Northwestern University, and Atsushi Inoue, Vanderbilt University
Ivan Canay is the HSBC Research Professor of Economics at Northwestern University. He earned his PhD in economics from the University of Wisconsin – Madison, and his research interests lie broadly in econometric theory and its applications. Part of his research has been about inference in partially identified models, inference with approximate randomization tests, experiments involving covariate-adaptive randomization, and inference with a small number of clustered data.

Atsushi Inoue is Cornelius Vanderbilt Chair and Professor of Economics at Vanderbilt University. He earned his PhD in economics from the University of Pennsylvania. His main research interests lie in time series econometrics. Specifically, he has been interested in issues of identification and inference in macroeconomic models.

Journal of Computational and Graphical Statistics (JCGS) Co-Editors
Galin Jones, University of Minnesota, and Faming Liang, Purdue University
Faming Liang is distinguished professor of statistics at Purdue University with research interests ranging from Markov chain Monte Carlo to machine learning to bioinformatics. He has been an ASA Fellow, an Institute of Mathematical Statistics fellow, and an elected member of the International Statistical Institute. He is also a co-winner of the 2017 Youden Prize.

Journal of Statistics and Data Science Education (JSDSE)
Nicholas Horton, Amherst College
Nicholas Horton is Beitzel Professor of Technology and Society (statistics and data science) at Amherst College. He co-chairs the National Academies Committee on Applied and Theoretical Statistics and has been involved in a number of data science initiatives. Horton previously served as an associate editor, section editor, and guest editor for the journal.

Statistics and Public Policy (SPP)
Aleksandra Slavković, Penn State University
Aleksandra (Seša) Slavković is a professor of statistics and associate dean for graduate education in the Eberly College of Science at Penn State. Her primary research focuses on statistical methodology for data privacy in the context of small- and large-scale surveys and health, genomic, and network data, including differential privacy and broad data access that offers guarantees of accurate statistical inference needed to support reliable science and policy. She is a fellow of the ASA, Institute of Mathematical Statistics, and International Statistical Institute; serves as an associate editor for the Annals of Applied Statistics and Journal of Privacy and Confidentiality; and is the 2022 chair of the ASA Social Statistics Section. She earned her PhD in statistics from Carnegie Mellon University.

Journal of Survey Statistics and Methodology (JSSAM)
Katherine J. Thompson, US Census Bureau
Katherine J. Thompson is a survey statistician with more than 30 years of professional experience. She is the senior mathematical statistician in the Associate Directorate for Economic Programs of the Census Bureau. Her practical and theoretical experience covers all areas of sample survey design, including sample selection, estimation, variance estimation, analysis, statistical data editing, imputation, and quality control. She has published research in and refereed for many journals and currently serves as associate editor of the Journal of Official Statistics. She was elected an ASA Fellow in 2017.

Journal of Nonparametric Statistics (JNPS)
Wenbin Lu, North Carolina State University
Wenbin Lu is professor of statistics at North Carolina State University. His research mainly focuses on semiparametric/nonparametric methods and inference, personalized medicine, causal inference, machine learning, and high-dimensional data analysis. He is an associate editor for Biostatistics, Biometrics, and Statistica Sinica and a fellow of the American Statistical Association.

Journal of Agricultural, Biological, and Environmental Statistics (JABES)
Jorge Mateu, Universitat Jaume I
Jorge Mateu earned a bachelor’s degree in 1992 from the University of Valencia (Spain) in mathematics and statistics and completed his PhD in statistics in 1998 from the same university under the supervision of Peter Diggle and Francisco Montes. He is a full professor of statistics in the department of mathematics at University Jaume I of Castellon (Spain). Mateu has expertise in stochastic processes in their wide sense, with a particular focus on spatial and spatio-temporal point processes, but also on geostatistics and areal spatial data. His research lies at the intersection of statistics, computational sciences, and natural and social sciences with a wide focus on data science. Large projects in crime data analysis and public health, where a combination of statistical methods and machine learning methods are at the core of the approach, are currently taking most of the time of his research group.

Mateu became an elected member of the International Statistical Institute in 2004 and fellow of the Royal Statistical Society in 2016.

He has published more than 250 papers in peer-reviewed international journals and organized several international conferences with a focus on modeling space-time processes. He sits on the editorial boards of JABES, Spatial Statistics, and Environmetrics.