Students/post-docs
Current students and post-docs
Wenlong Gong, Post-doc
Research interests: Spatial and spatio-temporal statistics, big data computational statistics, Gaussian processes, Bayesian inference.
Research interests: Spatial and spatio-temporal statistics, big data computational statistics, Gaussian processes, Bayesian inference.
Mohamed Abba, PhD student
Research interests: Bayesian statistics and deep learning.
Research interests: Bayesian statistics and deep learning.
Parker Trostle, PhD student
Research interests: Spatial and spatiotemporal statistics, particularly in applied contexts. My current project deals with modeling a large climate dataset where stationarity is not a reasonable assumption.
Research interests: Spatial and spatiotemporal statistics, particularly in applied contexts. My current project deals with modeling a large climate dataset where stationarity is not a reasonable assumption.
Zun Yin, PhD student
Research interests: My research focuses on spatial data analysis for extreme values. I develop computationally efficient predictive models and apply them to massive environmental datasets. Currently, I am working on a computer model emulator for extreme storm surge in Florida. I am also interested in Bayesian statistics with application to clinical data.
Research interests: My research focuses on spatial data analysis for extreme values. I develop computationally efficient predictive models and apply them to massive environmental datasets. Currently, I am working on a computer model emulator for extreme storm surge in Florida. I am also interested in Bayesian statistics with application to clinical data.
Laura Wendelberger, PhD student
Research interests: My research areas are in variable selection techniques which acknowledge model uncertainty and in Bayesian data fusion. I am particularly interested in applications in materials science.
Research interests: My research areas are in variable selection techniques which acknowledge model uncertainty and in Bayesian data fusion. I am particularly interested in applications in materials science.
Matt Miller, PhD student
Research interests: I am interested in developing Bayesian statistics methods for spatial data, and applying these methods to a variety of fields. In particular, I love collaborating with non-statisticians to apply our work in materials science and public policy settings.
Research interests: I am interested in developing Bayesian statistics methods for spatial data, and applying these methods to a variety of fields. In particular, I love collaborating with non-statisticians to apply our work in materials science and public policy settings.
Andrew Giffin, PhD student
Research interests: I’m interested in causal inference, especially as it applies to spatial data. More generally, I seek to use interpretable models to answer real-world questions from data. My current work develops methods to examine the spatial effect of wildfires on airborne particulates.
Research interests: I’m interested in causal inference, especially as it applies to spatial data. More generally, I seek to use interpretable models to answer real-world questions from data. My current work develops methods to examine the spatial effect of wildfires on airborne particulates.
Steven Xu, PhD student
Research interests: My research mainly focuses on developing flexible Bayesian quantile regression models. My current project combines nonparametric methods and approximate likelihood approach to simultaneously estimate multiple conditional quantiles. I am also interested in machine learning, forecasting and applications related to clinical trials.
Research interests: My research mainly focuses on developing flexible Bayesian quantile regression models. My current project combines nonparametric methods and approximate likelihood approach to simultaneously estimate multiple conditional quantiles. I am also interested in machine learning, forecasting and applications related to clinical trials.
Can Cui, PhD student
Research interests: My main research areas is the application of Bayesian models in high dimensional data. My current project is on Bayesian variable selection method to detect skewed sparse signals in high dimension. I am also interested in spatial statistics and machine learning.
Research interests: My main research areas is the application of Bayesian models in high dimensional data. My current project is on Bayesian variable selection method to detect skewed sparse signals in high dimension. I am also interested in spatial statistics and machine learning.
FORMER STUDENTS/POST-DOCS
Dave Huberman, PhD, 2020
Thesis title: Advances In Spatial Statistics For Ecological and Environmental Data
Maggie Mao, Post-doc, 2019-2020
Current position: eBay
Current position: eBay
Vianey Leos Barajas, Post-doc, 2019-2020
Current position: Assistant Professor, University of Toronto
Current position: Assistant Professor, University of Toronto
Suman Majumder, PhD, 2020
Thesis title: Spatiotemporal Inference and Applications for Large Datasets
Thesis title: Spatiotemporal Inference and Applications for Large Datasets
Current position: Post-doc, Harvard
Yuan Tian, PhD, 2020
Thesis title: Bayesian Semi-parametric Models in Extreme Value Analysis
Thesis title: Bayesian Semi-parametric Models in Extreme Value Analysis
Current position: Novartis
Qian Guan, PhD, 2019
Thesis title: Bayesian Methods for Optimal Treatment Allocation and Causal Inference
Thesis title: Bayesian Methods for Optimal Treatment Allocation and Causal Inference
Current position: Facebook
Yawen Guan, Post-doc, 2017-2019
Current position: Assistant Professor, University of Nebraska.
Current position: Assistant Professor, University of Nebraska.
Arnab Hazra, PhD, 2019
Thesis title: Spatiotemporal Modeling with Biomedical and Environmental Applications
Thesis title: Spatiotemporal Modeling with Biomedical and Environmental Applications
Current position: Post-doc, King Abdullah University of Science and Technology
An-Ting Jhuang, PhD, 2019
Thesis title: Spatial Signal Detection Using Continuous Shrinkage Priors
Thesis title: Spatial Signal Detection Using Continuous Shrinkage Priors
Current position: United Health Group
Rui Li, PhD, 2019
Thesis title: Machine Learning Methods for Uncertainty Estimation and Decision Making
Thesis title: Machine Learning Methods for Uncertainty Estimation and Decision Making
Current position: Facebook
Haoyu Wang, PhD, 2019
Thesis title: Advances and applications of nonparametric statistics
Thesis title: Advances and applications of nonparametric statistics
Current position: SAS
Munir Winkel, PhD, 2018
Thesis title: New Applications of Sequential Experimental Design
Thesis title: New Applications of Sequential Experimental Design
Current position: Post-doc, Swiss Tropical and Public Health Institute
Zhou Lan, PhD 2019
Thesis title: Spatial Modeling of Positive Definite Matrices and Its Applications to Diffusion Tensor Imaging
Thesis title: Spatial Modeling of Positive Definite Matrices and Its Applications to Diffusion Tensor Imaging
Current position: Senior statistician, Yale
Alexandra Larsen, PhD 2018
Thesis title: Spatial Methods for Quantifying the Impact of Wildfire Smoke on Air Quality in the U.S.
Thesis title: Spatial Methods for Quantifying the Impact of Wildfire Smoke on Air Quality in the U.S.
Current position: Statistician, Environmental Protection Agency
Indranil Sahoo, PhD 2018
Thesis title : Spatiotemporal Models for Physical Processes
Current position: Assistant Professor, Virginia Commonwealth University
Thesis title : Spatiotemporal Models for Physical Processes
Current position: Assistant Professor, Virginia Commonwealth University
Maggie Johnson, Post-doc, 2017-2019
Current position: NASA Jet Propulsion Laboratory
Current position: NASA Jet Propulsion Laboratory
Susheela Singh, PhD 2018
Thesis title : Bayesian Methods for Nonlinear and Discrete Data with Complex Dependence
Thesis title : Bayesian Methods for Nonlinear and Discrete Data with Complex Dependence
Current position: YouTube
Neal Grantham, PhD, 2017
Thesis title : Statistical Methods for High-Dimensional Microbiome Data from Next Generation Sequencing Technology
Current position: Apple
Thesis title : Statistical Methods for High-Dimensional Microbiome Data from Next Generation Sequencing Technology
Current position: Apple
Ran (Jennifer) Wei, PhD, 2017
Thesis title : Bayesian variable selection using continuous shrinkage priors for nonparametric models and non-Gaussian data
Current position: Eli Lilly
Thesis title : Bayesian variable selection using continuous shrinkage priors for nonparametric models and non-Gaussian data
Current position: Eli Lilly
Yen-Ning Huang, Post-doc, 2015-2017
Current position: Assistant Professor, University of Indiana
Current position: Assistant Professor, University of Indiana
Colin Peterson, PhD, 2016
Thesis title : Mean-Dependent Spatial Prediction Methods with Applications to Materials Sciences
Current position: Statistician, Environmental Protection Agency
Thesis title : Mean-Dependent Spatial Prediction Methods with Applications to Materials Sciences
Current position: Statistician, Environmental Protection Agency
Samuel Morris, PhD, 2016
Thesis title : Spatial Methods for Modeling Extreme and Rare Events
Current position: Google
Thesis title : Spatial Methods for Modeling Extreme and Rare Events
Current position: Google
Yan (Dora) Zhang, PhD, 2016
Thesis title : Bayesian Methods for High-dimensional Data
Current position: Assistant Professor, University of Hong Kong
Thesis title : Bayesian Methods for High-dimensional Data
Current position: Assistant Professor, University of Hong Kong
Deidra Coleman, PhD 2015
Thesis title: Advances in Significance Testing for Cluster Detection
Current position: Assistant Professor, Philander Smith College
Thesis title: Advances in Significance Testing for Cluster Detection
Current position: Assistant Professor, Philander Smith College
Alfredo Farjat, PhD, 2015
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 : Optimal Seed Deployment under Climate Change using Spatial Models and Prediction of Genetic Merit in Loblolly Pine
Current position: Biostatistician, Duke University
Ryan Parker, PhD, 2015
Thesis title : Efficient Computational Methods for Large Spatial Data
Current position: JMP, Portland Trail Blazers
Thesis title : Efficient Computational Methods for Large Spatial Data
Current position: JMP, Portland Trail Blazers
Earvin Balderama, Post-doc, 2014-2015
Current position: Assistant Professor, Fresno State University
Current position: Assistant Professor, Fresno State University
Ander Wilson, PhD, 2014
Thesis title : Advances in Bayesian Methods for High-Dimensional Environmental Data
Current position: Assistant Professor, Colorado State University
Thesis title : Advances in Bayesian Methods for High-Dimensional Environmental Data
Current position: Assistant Professor, Colorado State University
Luke Smith, PhD, 2014
Thesis title : Bayesian Quantile Regression in Biostatistical Applications
Current position: Amazon
Thesis title : Bayesian Quantile Regression in Biostatistical Applications
Current position: Amazon
Laura Boehm Vock, PhD, 2013
Thesis title : Bridge Models and Variable Selection Methods for Spatial Data
Current position: Assistant Professor, Gustavus Adolphus College
Thesis title : Bridge Models and Variable Selection Methods for Spatial Data
Current position: Assistant Professor, Gustavus Adolphus College