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Calder, Catherine (Kate)
No

Catherine (Kate) Calder

Professor, Department Chair, Statistics and Data Sciences
College of Natural Sciences, Department of Statistics and Data Sciences



calder@austin.utexas.edu

Phone: 512-475-8802

Office Location
WEL 5.216E

Postal Address
2317 SPEEDWAY
AUSTIN, TX 78712

Catherine (Kate) Calder joined the Statistics and Data Sciences faculty in 2019 and currently serves as department chair. Previously, she spent 16 years on the faculty of The Ohio State University. She served as an associate director (2015–2018) and co-director (2018–2019) of the Mathematical Biosciences Institute, an NSF Division of Mathematical Sciences Research Institute located on the Ohio State campus. She is currently an associate editor for the Annals of Applied Statistics and Bayesian Analysis and has served the profession through various elected roles in sections of the American Statistical Association (ASA) and in the International Society for Bayesian Analysis. Her research has been funded by the NIH, NSF, NASA, and other agencies and foundations. She received the ASA Section on Statistics and the Environment’s 2013 Young Investigator Award and was elected Fellow of the ASA in 2014. Dr. Calder's current research focuses on spatio-temporal statistics, Bayesian methods, and network analysis. Her work is motivated by applications in the environmental, social, and health sciences. 

Ph.D., Statistics, Duke University, 2003

My research focuses on the development of statistical models, along associated inferential techniques, for phenomena that exhibit complex dependencies, particularly when the dependencies are spatial and/or temporal in nature. I frequently employ the Bayesian hierarchical modeling paradigm in my research and regularly work on problems that are high dimensional and, consequently, computationally intensive. My methodological contributions have been in the areas of dimension reduction for spatio-temporal data, the development of covariate-driven nonstationary spatial models, data-augmentation algorithms for spatial generalized linear (mixed) models, latent space and matrix factorization models for two-mode networks, and model-based comparisons of networks.  Much of my research is motivated by applications in the environmental, social, and health sciences.  I currently collaborate with social scientists at Ohio State on the Adolescent Health and Development in Context Study, a longitudinal study of adolescents and their daily activity patterns.