The Statistics Group consists of William Navidi, Luis Tenorio, Reinhard Furrer, and Eva Furrer. Their general interests lie in the area of applications of statistics to the physical sciences.

Professor William Navidi received his Ph.D. from the University of California at Berkeley in 1986. He has published papers dealing with such diverse topics as adjusting the U.S. Census, methods for forensic DNA typing, models for predicting indoor levels of air pollution, estimating the risk of brain tumors from exposure to magnetic fields, determining evolutionary relationships among species, calibration of instruments for measuring pulmonary function, on optimal methods for positioning equipment in an open pit mine, and many others. He is currently working on the development of statistical methods for analyzing the performance of mobile computer networks, modeling the causes of variability in permeability coefficient measurements of chemical penetration of aqueous solutions across skin, and on the development of efficient methods for sampling in case-control studies.

Professor Luis Tenorio received his Ph.D. from the University of California at Berkeley in 1992. He has published papers on such topics as the statistics of the cosmic microwave background (CMB) radiation, denoising of gravity gradiometry data, and many others. He is currently working on geophysical inverse problems and on the development of seismic data processing methods. He is also working on statistical methods to analyze data from future CMB satellite measurements.

Professor Reinhard Furrer received his Ph.D. from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 2002, and completed a three year postdoctoral position at the National Center for Atmospheric Research (NCAR) in Boulder. He has published papers on such topics as atmosphere-ocean circulation models, estimation of prior and posterior covariance matrices in Kalman filter variants, and many others. His research interests include spatio-temporal geostatistics, state-space models, nonstationarity, large datasets, (ensemble) Kalman filter, extremes, multivariate and robust statistics. Currently, he works on fast and direct spatial interpolation techniques for large datasets and on spatial hierarchical Bayes in the context of atmosphere-ocean general circulation model (AOGCM) predictions.

Eva Furrer received her Ph.D. from the Swiss Federal Institute of Technology in Lausanne (EPFL). She is an adjunct professor in the Department of Mathematical and Computer Sciences at the Colorado School of Mines, and currently holds a post-doc position at the National Center for Atmospheric Research in Boulder. Her research interests include splines, generalized linear models, and experimental design.