Students/post-docs
Current students and post-docs

Research interests: Bayesian statistics and deep learning.

Research interests: Geostatistics, Bayesian inference, Extremal processes, Climate applications, High performance computing

Shih-Ni Prim, PhD Student
Research interests: Bayesian statistics and probabilistic machine learning.


Alvin Sheng, PhD Student
Nate Wiecha, PhD Student
Hongjian Yang, PhD Student
Research interests: spatial and temporal methods, data fusion, air pollution research
Matt Shisler, PhD Student
Research interests: machine learning, statistical computation, spatiotemporal methods
Brandon Feng, PhD Student
Research interests: Biostatistics, large datasets, spatial methods
Wei Zhao, PhD Student
Research interests: Statistical methods for inference in neuroscience and psychology, spatial statistics.
Elliot Maceda, PhD Student
Research interests: I am currently interested in the relationships and tradeoffs between mathematical models and statistical models. My current work centers around finding ways to save computation time using statistical emulators.
FORMER STUDENTS/POST-DOCS

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