Mason Statistics welcomes eight new faculty

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A great university is a machine of innovation. George Mason University's Department of Statistics at the new School of Computing welcomed new and returning faculty and students in August 2021. With highly anticipated 5-minute fever talks, eight new faculty hired during the pandemic (arriving during fall 2020 and fall 2021) showcased their diversified expertise. Current faculty also contributed to the talks. The School of Computing is part of  Mason's College of Engineering and Computing. “The research portfolios of these new faculty members are eye-catching, representing wide-ranging important fields in modern statistics and data science,” says Jiayang Sun, department chair.

The department is poised for major growth with new leadership, new hires, and new alliances. These include not only the regular statistics hires (at least four for fall 2022, see jobs.gmu.edu), but also the Tech Talent Investment Pipeline, a cluster hire in Computational Systems Biomedicine, potential joint positions with other departments, and organizational collaborations.

One of the organizational collaborations is the GMU Stat – InovaHealth Collaboration, among others. Inova Health is one of the leading hospital systems in the nation. The GMU-Inova alliance not only supports and encourages collaborative research but also helps young faculty establish a strong, versatile research portfolio.  As one of the newest faculty members, David Kepplinger, said, “the research culture at Mason and the statistics department, in particular, is built around the idea of collaboration.” He continues:  “Everyone is open to share ideas and join forces. There are many opportunities around campus and in the D.C. 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 at Mason, are:

Ben Seiyon Lee, assistant professor. Lee received his PhD from 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. Lee's most exciting project is calibrating a hydrological computer model on flash floods and inland flooding in central Pennsylvania. The goal is to understand how global warming affects the severity of inland floods and how those projections affect flood zones and insurance. He is involved with the Inova Health project.

 

David Kepplinger, assistant professor. Kepplinger received his PhD in Statistics from the University of British Columbia, and he is part of the 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 as well as countering the effects of contamination on predictive models.

Jonathan Auerbach, assistant professor. Auerbach received 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, traffic safety studies, and assessed the quality of the 2020 census during his stint as a science policy fellow at the American Statistical Association. 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 the City Council.

Lily Wang, professor.  Wang received her PhD in Statistics from Michigan State University. Her research interests include nonparametric statistics, semiparametric statistics, large and complex data sets and high-dimensional data, and official statistics. The methods she developed have a wide application 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 (2008), a Fellow of the Institute of Mathematical Statistics (2020), and a Fellow of the American Statistical Association (2021).

Mary Meyer, visiting professor, is on sabbatical leave from Colorado State University. Meyer received her PhD in Statistics from the University of Michigan. Her research is in nonparametric function estimation with shape constraints, quite well-known in her field of expertise for both methodological and computational contributions. She is the author SIAM textbook on Probability and Mathematical Statistics: Theory, Applications, and Practice in R (2019). She spent nine years at the University of Georgia Statistics Department before joining Colorado State University. She plays the piano beautifully.

Isuru Dassanayake, assistant professor (teaching).  Dassanayake received his PhD in Mathematics majoring in Statistics and a Master of Science 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, spatial data analysis, Bayesian Statistics, and high dimensional data analysis. His dissertation focused on exploring social and economic predictors for U.S. government elections using advanced statistical modeling and machine learning techniques. He is one of the examples in which our term teaching faculty also conduct research. He will play a major role in our mission of providing excellent statistics education to our students at all levels.

Kenneth Pasiah, assistant professor (teaching). Pasiah received 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 further develop the department’s undergraduate curriculum and engage in outreach to underserved communities and high-school students.

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

The Department of Statistics faculty members are internationally recognized experts whose research affects healthcare, economics, technology, clinical trials, and public policy. They are leaders in their statistical fields, and their work is published in high-quality, peer-reviewed journals. The department faculty expertise can be found here. We are looking forward to its continuous growth and development in both research and educational programs.

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