(* denotes PhD advisee, ** denotes current undergraduate student)
Submitted
Kowal, D. Regression with race-modifiers: towards equity and interpretability.
*Feldman, J. and Kowal, D. Bayesian Quantile Regression with Subset Selection: A Posterior Summarization Perspective.
*Zito, J. and Kowal, D. The projected dynamic linear model for time series on the sphere.
*Liu, C., Kowal, D., Doss-Gollin, J., and Vannucci, M. Dynamic Bayesian Functional Graphical Models with Application to Sea Surface Temperature Data.
Kowal, D. and Wu, B. Monte Carlo inference for semiparametric Bayesian regression.
*Sun, T. and Kowal, D. Ultra-efficient MCMC for Bayesian longitudinal functional data analysis.
*Feldman, J. and Kowal, D. Nonparametric Copula Models for Multivariate, Mixed, and Missing Data.
Student Paper Award (Feldman): Section on Bayesian Statistical Science (2023)
Student Paper Award (Feldman): Survey Research Methods, Government Statistics, and Social Statistics Sections (2023, declined)
Kowal, D. and **Wu, B. Semiparametric discrete data regression with Monte Carlo inference and prediction.
Published/In Press
Kowal, D. and Canale, A. (2024). Semiparametric Functional Factor Models with Bayesian Rank Selection. Bayesian Analysis.
Economics, Finance, and Business (EFaB) Presentation Award: European Seminar on Bayesian Econometrics (2021)
*Gao, Y. and Kowal, D. (2024). Bayesian adaptive and interpretable functional regression for exposure profiles. Annals of Applied Statistics.
Student Paper Award (Gao): Section on Bayesian Statistical Science (2023)
*King, B. and Kowal, D. (2023). Warped Dynamic Linear Models for Time Series of Counts. Bayesian Analysis.
Student Paper Award (King): Section on Bayesian Statistical Science (2022)
Student Paper Award (King): Business and Economic Statistics Section (2022, declined)
Distinguished Student Paper Award (King): International Biometric Society ENAR Spring Meeting (2022)
*Liu, C., Kowal, D., and Vannucci, M. (2022). Dynamic and Robust Bayesian Graphical Models. Statistics and Computing.
Student Paper Award (Liu): Business and Economic Statistics Section (2021)
Kowal, D. (2022). Subset selection for linear mixed models. Biometrics.
Kowal, D. and **Wu, B. (2022). Semiparametric count data regression for self-reported mental health. Biometrics.
*Feldman, J. and Kowal, D. (2022). Bayesian Data Synthesis and the Utility-Risk Trade-Off for Mixed Epidemiological Data. Annals of Applied Statistics.
Student Paper Award (Feldman): Health Policy Statistics Section (2022)
Bravo, M., Zephyr, D., Kowal, D., Ensor, K., and Miranda, M. L. (2022). Racial residential segregation shapes relationships between early childhood lead exposure and 4th grade standardized test scores. Proceedings of the National Academy of Sciences.
Kowal, D. (2022). Bayesian subset selection and variable importance for interpretable prediction and classification. Journal of Machine Learning Research.
Karand, J., Reis, K., Ponsiano, S., **Gargurevich, N., **Zhou, J., Fadhil, S., Razac, Y., Rosengard, R., Kowal, D., and Peck, R. (2021). Sex-Dependent Correlates of Arterial Stiffness in Tanzanian Adults. Tropical Medicine & International Health.
Kowal, D., Bravo, M., Leong, H., Bui, A., Griffin, R. J., Ensor, K. B., and Miranda, M. L. (2021). Bayesian Variable Selection for Understanding Mixtures in Environmental Exposures. Statistics in Medicine.
Kowal, D. (2021). Fast, Optimal, and Targeted Predictions using Parametrized Decision Analysis. Journal of the American Statistical Association.
Kowal, D. (2021). Dynamic Regression Models for Time-Ordered Functional Data. Bayesian Analysis.
Kowal, D. and Canale, A. (2020). Simultaneous transformation and rounding (STAR) models for integer-valued data. Electronic Journal of Statistics.
Miao, Y., Kowal, D., Panchal, N., Vila, J., and Vannucci, M. (2020). Nonlinear state-space modeling approaches to real-time autonomous geosteering. Journal of Petroleum Science and Engineering.
Kowal, D. and *Bourgeois, D. (2020). Bayesian Function-on-Scalars Regression for High Dimensional Data. Journal of Computational and Graphical Statistics.
Wu, M., Miao, Y., Panchal, N., Kowal, D., Vannucci, M., Vila, J., and Liang, F. (2019). Stochastic Clustering and Pattern Matching for Real Time Geosteering. Geophysics.
Kowal, D. (2019). Integer-Valued Functional Data Analysis for Measles Forecasting. Biometrics.
Kowal, D., Matteson, D.S., and Ruppert, D. (2019). Dynamic Shrinkage Processes. Journal of the Royal Statistical Society, Series B.
Student Paper Award: Business and Economic Statistics Section (2018)
Kowal, D., Matteson, D.S., and Ruppert, D. (2017). Functional autoregression for sparsely sampled data. Journal of Business & Economic Statistics.
Student Paper Award: Nonparametric Statistics Section (2017)
Kowal, D., Matteson, D.S., and Ruppert, D. (2017). A Bayesian multivariate functional dynamic linear model. Journal of the American Statistical Association.
Student Paper Award: Section on Bayesian Statistical Science (2016)
Kohn, J.C., Chen, A., Cheng, S., Kowal, D., King, M.R., and Reinhart-King, C.A. (2016). Mechanical heterogeneities in the subendothelial matrix develop with age and decrease with exercise. Journal of Biomechanics, 49(9), 1447-1453.
Alcoser, T.A., Bordeleau, F., Carey, S.P., Lampi, M.C., Kowal, D., Somasegar, S., Varma, S., Shin, S.J., and Reinhart-King, C.A. (2015). Probing the biophysical properties of primary breast tumor-derived fibroblasts. Cellular and Molecular Bioengineering, 8(1), 76-85.
Editors’ Choice Award: Cellular and Molecular Bioengineering (2016)
Technical Reports
Kowal, D. A Modified Ljung-Box Test for the Functional Linear Model.
Kowal, D. and Ding, J. (2012). Applications of linear mixed effect models: an analysis of Missouri school data. Washington U. Senior Honors Thesis Abstracts.
Kowal, D. (2009). Methods of capturing stereoscopic movies, their uses, and their limitations. NASA Space Grant Consortium.