About the Speakers
Roger Bivand is a British geographer educated at Cambridge and the LSE, and is Professor of Geography in the Department of Economics at NHH Norwegian School of Economics. He is active in development of contributed software for analysing spatial data using the R statistical language, and is an Ordinary Member of the R foundation. Coordination of an international community of scientists numbering thousands using R for spatial data analysis constitutes his main academic contribution, associated with a book on the same theme written with Edzer Pebesma and Virgilio Gómez-Rubio. He has published over 20 peer-reviewed articles in scientific journals, in addition to book chapters and other work. He writes and maintains R contributed packages for applied spatial data analysis. He is an editor of the Journal of Statistical Software, and a member of the editorial board of Journal of Geographical Systems.
Konstantin Krivoruchko is a senior research associate on the ESRI software development team who played a central role in developing ArcGIS Geostatistical Analyst. Prior to joining ESRI in 1998, he was director of the GIS laboratory at the Sakharov Institute of Radioecology in Minsk, Belarus, where he developed GIS and spatial statistics curriculum, supervised PhD and graduate school candidate research pertaining to GIS applications and spatial statistical data analysis. In 1997-1998 Konstantin Krivoruchko served as a member of the Belorussian Governmental Commission on Chernobyl Accident. From 1989 to 1994, Konstantin Krivoruchko functioned as the division chief of the Physics Department at the Belarussian National Academy of Sciences, Nuclear Power Institute, where he focused on problems of radioecology and epidemiology. His work was largely devoted to the statistical analysis of Chernobyl-related radioecological and epidemiological data. Konstantin Krivoruchko has taught numerous workshops and lecture courses on applied spatial statistics and GIS in the USA, Austria, Spain, and Japan. The draft version of the book Spatial Statistical Data Analysis for GIS Users has been used in the UNIGIS Master’s of Science program (http://salzburg.unigis.net/msc/compulsory-modules) for five years and a large number of GIS professionals were introduced to the statistical data analysis through this book. 600 copies of this book were sold in the first six months after the publication on April 25, 2011.
Håvard Rue will not be able to come to the winter conference and instead one of his collaborators since several years, Daniel Simpson, will give lectures and exercises on r-inla. Gaussian Markov random fields (GMRF) models, is a main ingredient doing (fast and accurate) approximate Bayesian analysis for latent Gaussian models using integrated nested Laplace approximations (INLA). The webpapge www.r-inla.org provides an R-interface to the INLA methodology. The recent research interest is taking GMRFs into geostatistics using stochastic partial differential equations as the bridge, which provides an explicit link between certain Gaussian fields and GMRFs in triangulated lattices.
