My research focus is the design and analysis of clinical trials and observational studies. In addition to collaborative research, I am also interested in developing methods for longitudinal data analysis and Bayesian modeling.
PhD, Statistics, The Ohio State University
MS, Statistics, The Ohio State University
BS, Mathematics, Duquesne University
Matuk, J., Kurtek, S., & Bharath, K. (2024). Topo-Geometric Analysis of Variability in Point Clouds using Persistence Landscapes. IEEE Transactions on Pattern Analysis and Machine Intelligence.
Matuk, J., Bharath, K., Chkrebtii, O., & Kurtek, S. (2022). Bayesian framework for simultaneous registration and estimation of noisy, sparse, and fragmented functional data. Journal of the American Statistical Association, 117(540), 1964-1980.
Matuk, J., & Guo, X. (2022). Shape-restricted estimation and spatial clustering of COVID-19 infection rate curves. Spatial Statistics, 49, 100546.
Matuk, J., Bharath, K., Chkrebtii, O., & Kurtek, S. (2021). Geometric empirical Bayesian model for classification of functional data under diverse sampling regimes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4434-4442).
Matuk, J., Mohammed, S., Kurtek, S., & Bharath, K. (2020). Biomedical applications of geometric functional data analysis. Handbook of variational methods for nonlinear geometric data, 675-701.
