Appointments and research interests

I am an assistant professor at Michigan State University with a joint appointment in the Departments of Forestry and Geography, and am adjunct in the Department of Statistics & Probability. I am also a member of the interdisciplinary Ecology, Evolutionary Biology, and Behavior Graduate Program faculty.

My research interests lie in developing methodologies for monitoring and modeling environmental processes, Bayesian statistics, spatial statistics, and statistical computing. A central theme in my research is the use of hierarchical models to integrate information from disparate sources to improve inference and prediction. In terms of application areas, my research focuses on spatial-temporal modeling of changing ecosystem components and systems. My recent interest is in improving frameworks for modeling exposure to pollutants, climate change, and health outcomes (ecosystem and public).

Upcoming and recent courses and workshops

International Workshop on Spatio-Temporal Modelling, September 12 - 14, 2012, Guimarães, Portugal

The Research Centre of Mathematics, Minho University, will host the VI International Workshop on Spatio-Temporal Modeling (METMAVI). The scientific program hosts invited and contributed sessions covering topics on the latest in theory, methods and applications.→ Details

GEOMED, October 20 - 22, 2011, Victoria, BC, Canada

GEOMED 2011 is the 7-th international, interdisciplinary conference on spatial statistics and geomedical systems. GEOMED brings together statisticians, geographers, epidemiologists, computer scientists, and public health professionals to discuss methods of spatial analysis, as well as present and debate the results of such analyses. I will give an invited talk entitled "Bayesian dynamic modeling for large space-time datasets using Gaussian predictive processes." → Details

Case Studies in Bayesian Statistics and Machine Learning, October 14 - 15, 2011, Carnegie Mellon University Pittsburgh, PA

The workshop will focus on applications of Bayesian statistics and Machine Learning to problems in science and technology. The workshop builds upon the Case Studies in Bayesian Statistics Workshop which was held at CMU for the last two decades. My colleague Sudipto Banerjee and I will give an invited case study entitled "Advances in hierarchical spatial models for mapping forest attributes across large domains." → Details

Geography 890, Spring 2011

Hierarchical Bayesian Models for Environmental Spatial Data Analysis

This course explores recent advancements in hierarchical random effects models using Markov chain Monte Carlo (MCMC) methods. The focus is on linear and generalized linear modeling frameworks that accommodate spatial and temporal associations. The course blends modeling, computing, and data analysis including an introduction to the R statistical environment. Special attention is given to exploration and visualization of spatial-temporal data and the practical and accessible implementation of spatial-temporal models. → Details

Statistical Issues in Forest Management, May 2 - 4, 2011, Université Laval, Québec, Canada

Spatial statistics and forest inventories

The workshop covers advances in model-based and design-based estimation procedures, non-parametric models and smoothing methods, spatial modeling and nearest neighbor imputation, and post-stratification. I'll give a talk entitled "Advances in hierarchical spatial models for quantifying forest attributes." Should be a very good mix of participants. → Details