People

Brady T. West

CSCAR@ISR Director and ISR Faculty Lead

Brady worked for the old model of CSCAR as a Masters student in the Department of Statistics from 2001-2002. He fell in love with the service goals and overarching philosophy of CSCAR during this time, and joined CSCAR in 2003 as a consulting statistician after earning an MA in Applied Statistics. He worked full-time for CSCAR for the next five years before returning to Michigan for a PhD in Survey and Data Science in 2008. He continued working for CSCAR during his PhD studies, and joined ISR as a faculty member in the Survey Methodology Program of the Survey Research Center after earning his PhD in late 2011. He would continue to provide consulting services for CSCAR until 2018. He later became a Research Professor (by dry appointment) in the Department of Biostatistics at the U of M School of Public Health in 2023. Now an elected Fellow of the American Statistical Association and a named Collegiate Research Professor at ISR and Biostatistics, he is the author of 9 books on statistical methods and survey methodology and more than 240 peer-reviewed journal articles in applied statistics, survey methods, and public health. Brady currently serves as the Overall Director of CSCAR@ISR.

Brady T. West's CV (PDF)

Paul Burton

Statistical and Survey Methodology Consultant

Paul Burton is a statistician with nearly 20 years of experience working in survey research organizations, the last 12 of which were spent at the University of Michigan's Survey Research Operations. His work has focused on the design, implementation, and analysis of complex samples for large-scale national studies, including the Health and Retirement Study, the National Survey of Family Growth, and the American National Election Study. He has extensive experience consulting with principal investigators and research teams on statistical methodology, survey design, data collection strategies, and the use of Census, geographic, and commercial data to improve sampling efficiency and reach hard-to-reach populations.

Paul holds a B.S. in Food and Bioprocess Engineering from the University of Illinois at Urbana-Champaign and an M.A. in Public Administration from Michigan State University, where he also completed doctoral coursework in statistical methodology and American politics.

Matt Zawistowski

Biostatistics Faculty Lead

Matthew Zawistowski is a Clinical Associate Professor of Biostatistics. Matt completed his dissertation and postdoc in Biostatistics at the University of Michigan, focusing on problems in statistical and population genetics, including the design and analysis of large-scale genome sequencing studies for a range of complex diseases. Following his postdoc, Matt worked briefly at the Ann Arbor VA where he gained valuable hands-on experience building clinical phenotypes from Electronic Health Records. He returned to UM to contribute his expertise in genetics and EHR to the Michigan Genomics Initiative (MGI), a biobank of linked genetic and clinical data for Michigan Medicine patients. For several years Matt served as a statistical consultant for UM faculty seeking to incorporate MGI into their own research. Beyond research, Matt is passionate about teaching math and statistics. He is the Director of the Department of Biostatistics Big Data Summer Institute and was awarded the 2022 SPH Excellence in Teaching award.

Matthew Zawistowski's CV (PDF)

Abigail Mauger

PhD Student in Biostatistics

Abigail Mauger is a PhD candidate in Biostatistics at the University of Michigan. She earned her M.S. in Biostatistics from the University of Michigan in 2024 and her B.S. in Biochemistry and Molecular Biology from Pennsylvania State University in 2022. Her research interests include analysis of single cell -omics data and the development of methods for statistical genetics/genomics applications.

Johann Gagnon-Bartsch

Statistics Faculty Lead

Johann Gagnon-Bartsch is an Associate Professor in the department of Statistics. He looks forward to assisting with all aspects of statistical practice, from study design to modeling to ensuring final results are reproducible. His own research focuses on causal inference, machine learning, and nonparametric methods with applications in the biological and social sciences.

Jaylin Lowe

PhD Student in Statistics

Jaylin Lowe is a fifth year Ph.D. student in Statistics at the University of Michigan. Her research interests include causal inference, survey methodology, and machine learning with applications to the social sciences.