Students/post-docs
Current students and post-docs
Henry Uddyback, PhD Student
My research interests include Bayesian inference, spatial statistics, and spatial transcriptomics.
Sarthi Patel, PhD Student
My research interests include spatial statistics, causal inference, and applications in environmental studies.
Jingyi Hao, PhD Student
My research interests include functional data analysis, causal inference and biostatistical applications.
Xiaodan Zhou, PhD Student
My research interests include causal inference, machine learning and spatiotemporal modeling.
Shih-Ni Prim, PhD Student
My research interests include Bayesian inference, spatial statistics, surrogate modeling, and applications in environmental studies.
Ryan Li, PhD Student
Matt Shisler, PhD Student
Research interests: machine learning, statistical computation, spatiotemporal methods
Wei Zhao, PhD Student
Research interests: Statistical methods for inference in neuroscience and psychology, spatial statistics.
Elliot Maceda, PhD Student
Research Interests: (1) Bayesian parameter estimation and uncertainty quantification in complex, intractable mathematical models using simulation-based inference and variational inference. (2) Using data from those mathematical models to improve the predictive power of machine learning models.
Connor McNeill, PhD Student
Research Interests: Spatial modeling, Bayesian inference, and Statistical epidemiology
Shi Cen, PhD Student
Research Interests: My research interests lie in statistical phylogenetics and phylodynamics, with a current focus on parameter inference in multi-type birth-death models using Bayesian methodologies, and Bayesian parameter estimation using simulation-based inference.
Sean O’Connor, PhD Student
Research interests: Bayesian inference, uncertainty quantification, spatial statistics, and applications in environmental statistics.
Hongjian Yang, PhD Student
Research interests: spatial and temporal methods, data fusion, air pollution research
FORMER STUDENTS/POST-DOCS
Brandon Feng, PhD, 2026
Thesis title: Adaptive Uncertainty Quantification Methods for Machine Learning
Current position: Amazon
Dongjae Son, PhD, 2025
Nate Wiecha, PhD, 2025
Alvin Sheng, PhD, 2024
Eric Yanchenko, PhD, 2023
Thesis title: Bayesian Methodologies for the Spatial Spread of Disease
Thesis title: Robust Statistical Methods for Model Selection and Land Cover Change Monitoring
Thesis title: Bayesian Methods for Large Spatial Data Sets with Materials and Environmental Science Applications
Thesis title: Methods for Causal Inference on Spatial Data with Environmental and Public Health Applications
Thesis title: Advances in Semiparametric Quantile Regression
Current position: University of Houston
Thesis title: Advanced Methods in Bayesian Variable Selection and Causal Inference
Dave Huberman, PhD, 2020
Thesis title: Advances In Spatial Statistics For Ecological and Environmental Data
Current position: Palo Alto VA Medical Center
Current position: eBay
Current position: Assistant Professor, University of Toronto
Thesis title: Spatiotemporal Inference and Applications for Large Datasets
Thesis title: Bayesian Semi-parametric Models in Extreme Value Analysis
Thesis title: Bayesian Methods for Optimal Treatment Allocation and Causal Inference
Current position: Assistant Professor, University of Nebraska.
Thesis title: Spatiotemporal Modeling with Biomedical and Environmental Applications
Thesis title: Spatial Signal Detection Using Continuous Shrinkage Priors
Thesis title: Machine Learning Methods for Uncertainty Estimation and Decision Making
Thesis title: Advances and applications of nonparametric statistics
Thesis title: New Applications of Sequential Experimental Design
Thesis title: Spatial Modeling of Positive Definite Matrices and Its Applications to Diffusion Tensor Imaging
Thesis title: Spatial Methods for Quantifying the Impact of Wildfire Smoke on Air Quality in the U.S.
Thesis title : Spatiotemporal Models for Physical Processes
Current position: Assistant Professor, Virginia Commonwealth University
Current position: NASA Jet Propulsion Laboratory
Thesis title : Bayesian Methods for Nonlinear and Discrete Data with Complex Dependence
Thesis title : Statistical Methods for High-Dimensional Microbiome Data from Next Generation Sequencing Technology
Current position: Apple
Thesis title : Bayesian variable selection using continuous shrinkage priors for nonparametric models and non-Gaussian data
Current position: Eli Lilly
Current position: Assistant Professor, University of Indiana
Thesis title : Mean-Dependent Spatial Prediction Methods with Applications to Materials Sciences
Current position: Statistician, Environmental Protection Agency
Thesis title : Spatial Methods for Modeling Extreme and Rare Events
Current position: Google
Thesis title : Bayesian Methods for High-dimensional Data
Current position: Assistant Professor, University of Hong Kong
Thesis title: Advances in Significance Testing for Cluster Detection
Current position: Assistant Professor, Philander Smith College
Thesis title : Optimal Seed Deployment under Climate Change using Spatial Models and Prediction of Genetic Merit in Loblolly Pine
Current position: Biostatistician, Duke University
Thesis title : Efficient Computational Methods for Large Spatial Data
Current position: JMP, Portland Trail Blazers
Current position: Assistant Professor, Fresno State University
Thesis title : Advances in Bayesian Methods for High-Dimensional Environmental Data
Current position: Assistant Professor, Colorado State University
Thesis title : Bayesian Quantile Regression in Biostatistical Applications
Current position: Amazon
Thesis title : Bridge Models and Variable Selection Methods for Spatial Data
Current position: Assistant Professor, Gustavus Adolphus College