Department Directory

Office: Gates Hall 340

In the office Tuesday-Thursday; remote on Monday and Friday

Erika joined the CSCU staff in the fall of 2013. She has a PhD in Ecology (Botany Department) and an MS in Biometry (Statistics Department) from the University of Wisconsin – Madison. Her research there focused on community ecology and spatial ecology of forest understory plants. She was also a postdoc at Iowa State University, working on landscape ecology and spatial modeling of invasive desert species and their relationship with fire risk. Her research interests include multivariate and spatial analysis, data visualization, data management and reproducible research. Erika was a participant in the inaugural Summer Institute 2013 at the National Center for Ecological Analysis and Synthesis.

Stephen joined the CSCU in the summer of 2015. He has a M.S. in mathematics from Missouri State University and a M.S. in statistics from Syracuse University. He has held several teaching positions in the mathematics departments of near-by colleges, and now enjoys teaching workshops on a variety of statistical concepts. Stephen is interested in statistical applications relating to nutrition, sociology, psychology, and linguistics and regularly consults with clients on a broad range of topics including, but not limited to, structural equation modeling, generalized linear mixed models, and data reduction techniques. He has been published in the Journal of Public Health, PLoS ONE, and Obesity.

Matt Thomas joined the CSCU in 2022 and was excited to return to Cornell where he completed his B.A. in mathematics in 2006. Matt has an M.S. and a Ph.D. in mathematics from the University of Arizona, where he focused on quantitative mathematics education, and held faculty positions at the University of Central Arkansas and Ithaca College. Matt’s enthusiasm for statistics springs from the diversity of methods he has applied to his own research, including item response theory and psychometric methods for evaluating student performance in calculus, qualitative and mixed methods approaches to understanding how mathematicians and learners use algorithmic thinking, and using machine learning techniques to make predictions about the composition date of American folk dances. Matt is interested in issues of measurement and causal inference and appreciates the nuance and challenges of data manipulation and management. He enjoys teaching statistics and coding, and looks forward to working with a clients on a range of topics including, but not limited to, psychometric and item response theory models, mixed models, structural equation models, and experimental design.