Martha Bushong, Brett Hunter, David Kepplinger, Inchi Hu, and Jiayang Sun

The George Mason University (GMU) Department of Statistics at the new school of computing welcomed eight new faculty hired during the pandemic (arriving during fall 2020 and fall 2021). “The research portfolios of these new faculty members are excellent, representing wide-ranging important fields in modern statistics and data science,” said Jiayang Sun, department chair. The school of computing is part of the college of engineering and computing.

The department is poised for growth. David Kepplinger, a new hire, said, “The research culture at Mason and the statistics department, in particular, is built around the idea of collaboration. Everyone is open to sharing ideas and joining forces. There are many opportunities around campus and in the DC area to work with experts from diverse fields and translate our statistical research into practice— leveraging our expertise in methodology, theory, and computation—to open the doors for impactful scientific discoveries.”

New faculty, listed in chronological order of their arrival, include the following:

Ben Seiyon Lee, assistant professor, earned his PhD from The Pennsylvania State University. His research interests include computational methods for modeling high-dimensional spatial-temporal data, statistical methods and algorithms for calibrating complex computer models, and interdisciplinary research in the environmental sciences. He is particularly interested in developing scalable methods to model various types of massive spatio-temporal data sets and statistical methods for studying climate change. He is involved with the GMU / Inova Health project.

David Kepplinger, assistant professor, earned his PhD in statistics from the University of British Columbia and is also part of the GMU / Inova Health collaboration. His research primarily revolves around robust estimation in high-dimensional settings and applications in the life sciences. Kepplinger is particularly interested in the robustness of feature selection in the presence of arbitrary contamination and countering the effects of contamination on predictive models.

Jonathan Auerbach, assistant professor, earned his PhD in statistics from Columbia University. His research covers a wide range of topics at the intersection of statistics and public policy. He has measured selection bias in mortality studies and traffic safety studies and, as a science policy fellow at the American Statistical Association, assessed the quality of the 2020 Census data. His work also investigates urban myths. He has broad methodological interests in the analysis of longitudinal data, particularly for data science and causal inference. His policy interests include urban analytics; open data; and the collection, evaluation, and communication of official statistics. Auerbach was also a researcher at the Center for Urban Research at the City University of New York and an analyst for New York City’s legislature and city council.

Lily Wang, professor, earned her PhD in statistics from Michigan State University. Her research interests include non-semiparametric regression, statistical learning of data objects with complex features, methodologies for functional data, spatio-temporal data, survey sampling, and data reduction methods. The methods she developed have applications in economics, engineering, neuroimaging, epidemiology, environmental studies, official statistics, and biomedical science. Prior to joining Mason, she was on the faculty of Iowa State University and the University of Georgia. Wang is an elected member of the International Statistical Institute, a fellow of the Institute of Mathematical Statistics, and a fellow of the American Statistical Association.

Mary Meyer, visiting professor, is on sabbatical leave from Colorado State University. Meyer earned her PhD in statistics from the University of Michigan. Her research is in nonparametric function estimation with shape constraints, and she is well-known in her field of expertise for both methodological and computational contributions. Meyer is the author of Probability and Mathematical Statistics: Theory, Applications, and Practice in R. She spent nine years at the University of Georgia statistics department before joining Colorado State University.

Isuru Dassanayake, assistant professor, earned his PhD in mathematics, majoring in statistics, from Texas Tech University. Although his position is focused on teaching, his research interests have included machine learning, statistical computing, heteroscedastic mixed effects models, and high-dimensional data analysis. His dissertation focused on exploring social and economic predictors for US government elections using advanced statistical modeling and machine learning techniques.

Kenneth Pasiah, assistant professor, earned his PhD in applied statistics from the University of Memphis. His research interests include random number generation and applied statistics. His most exciting research project was the study of large-order multiple recursive generators (MRGs). The goal of this project was to create an efficient method to accelerate the computer search of large-order MRGs. At Mason, his primary role will be to contribute to the department’s undergraduate curriculum and engage in outreach to underserved communities and high-school students.

Inchi Hu, professor, earned his PhD in statistics from Stanford University. Previously, he was a faculty member at the University of Maryland College Park and University of Pennsylvania and a chair professor at Hong Kong University of Science and Technology. His current research explores the interface between statistics and machine learning such as stochastic approximation versus reinforcement learning and empirical Bayes versus variational autoencoder. He is an elected fellow of the Institute of Mathematical Statistics. At Mason, he also assists with data science-economics initiatives and serves on the department’s research task force.

GMU is Virginia’s largest public research university. The department of statistics faculty members are internationally recognized experts whose research affects health care, economics, technology, clinical trials, and public policy. Read about the department faculty expertise.