Chris Paciorek, Carnegie Mellon University
A class of convolution-based nonstationary covariance functions

Isin Ozaksoy, North Carolina State University
Evaluation of the seismic activities of Turkey

Marco Ferreira, DME - Universidade Federal do Rio de Janeiro
Bayesian Inference for Proper Gaussian Markov Random Fields

Kate Calder, Duke University
Exploring Latent Structure in Multivariate Spatial Temporal Processes using Process Convolutions

Jun Zhu, University of Wisconsin - Madison
A Multiresolution Tree-Structure Spatial Linear Model

Zhengyuan Zhu, University of North Carolina
Optimal Sampling Design for Gaussian Random Fields

John Holt, University of Guelph
Multiple testing in environmental epidemiology - A case study
and
Spatial and temporal modeling of sleeping sickness in South-East Uganda

Poster Session - Tuesday

Jonathan Stroud, University of Pennsylvania
Space-time Modeling of Mexico City Ozone Levels
(joint with G. Huerta, University of New Mexico and B. Sanso, University of California at Santa Cruz)

Yulia Gel, University of Washington
Accessing uncertainty in numerical mesoscale weather prediction via ensembles of forecasts
(joint with A. Raferty and T. Gneiting, University of Washington

Dana Draghicescu, University of Chicago
A model for spatio-temporal prediction of ground-level ozone mixing ratios
(joint work with V. Dukic, G. Eshel, J. Frederick, E. Naureckas, P. Rathouz, M. Stein, and A. Zubrow, University of Chicago)

Li Chen, North Carolina State University
Spatial-temporal modeling for wind data (joint with M. Fuentes and J. M. Davis, North Carolina State University)

Serge Guillas, CISES, University of Chicago
Space-time modeling of stratospheric ozone

Jaechoul Lee, University of Georgia
Trends in United States Temperature Extremes

Anders Malmberg, University of Lund
A real-time assimilation model for near-surface ocean winds

Poster Session - Wednesday

Bruno Sanso, University of California at Santa Cruz
Spatio-temporal models based on discrete convolutions
(joint with A. Schmidt)

Daniel Fink and Marty Wells, Cornell University
Adaptive Multi-Order Penalized Splines

Sandra McBride, Duke University
Hiearchical Bayesian Calibration: An Application to Ambient Air Pollution Measurement Data