Dustin Pluta

Dustin Pluta is an Assistant Professor in the Department of Biostatistics, Data Science, & Epidemiology at the School of Public Health, Augusta University. His academic work bridges biostatistics, neuroimaging, and data science, with a focus on developing advanced statistical methods for neuroscience and public health applications.

Education:

• Ph.D. in Statistics, University of California, Irvine, 2020
• M.S. in Applied Statistics, California State University, Long Beach, 2015
• M.A. in Mathematics, University of California, Davis, 2008

His research interests lie at the intersection of biostatistics, functional brain connectivity, Bayesian modeling, and imaging genetics. He develops and applies statistical techniques to improve the quality and interpretability of neuroimaging data, particularly in the context of mental health and addiction behaviors. His work often involves Gaussian processes, penalized regression, and multivariate association testing.

The recent publications reflect a strong trend in neuroimaging statistics, with emphasis on enhancing trial-level ERP analysis, modeling dynamic functional connectivity, and integrating genetic and brain imaging data. These works span disciplines including neuroscience, psychiatry, and biostatistics, demonstrating methodological innovation and application to real-world health problems such as e-cigarette use vulnerability.

Scientific Awards and Honors:

• Distinguished Student Paper Competition Award, ENAR, International Biometric Society, 2018
• Student Paper Competition Award, Joint Statistical Meetings, Statistics in Imaging, 2018
• Robert L. Newcomb Memorial Endowed Graduate Student Award, UC Irvine, 2016
• Summer Fellowship, UC Irvine, 2016
• Chair’s Award, UC Irvine Department of Statistics, 2015

Dustin Pluta is actively involved in academic service, including serving as Committee Chair of the Journal Club and participating in faculty hiring and departmental meetings. He is also a reviewer for the journal Psychophysiology. He teaches graduate courses such as Applied Linear Models, Modern Methods of Multivariate Analysis, and the Data Science Capstone. While specific grant funding is not listed, his research output suggests active engagement in sponsored scholarly work.

He contributes to a collaborative research environment within the Department of Biostatistics, Data Science, & Epidemiology, where interdisciplinary projects involving neuroscience, public health, and data science are central to the academic mission.