CBMS Regional Conference in the Mathematical Sciences
University of California Santa Cruz, August 14-18, 2017
Hierarchical Bayesian methods for modeling spatial and space-time data constitute an extremely important, topical area of research in the statistical sciences, with a wide range of applications. However, the explosive growth of all areas in spatial and spato-temporal modeling have produced a massive body of lietarture which can be daunting for newcomers imposing a steep entry barrier into the field. This conference will provide a comprehensive review of Bayesian methods for spatial statistics by a highly distinguished statistician who has contributed foundational research in the field over the past twenty years.
The main lecturer for the conference will be Alan E. Gelfand, who is J.B. Duke Professor of Statistics and Decision Sciences at the Department of Statistical Science, Duke University. It is hard to find someone better suited to present a clear articulation of the field of Bayesian modeling for spatial and spatio-temporal data than Alan E. Gelfand. He is one of the most influential researchers in the area with lifelong work on the topic. Professor Gelfand will deliver ten two-hour lectures. In addition to the lectures, three invited speakers will deliver complementary two-hour lectures. These are Sudipto Banerjee (University of Califonia, Los Angeles), Michele Guindani (University of California, Irvine) and Christopher Paciorek (University of California, Berkeley). The conference will be hosted by the Department of Applied Mathematics and Statistics of the Baskin School of Engineering. The local organizers are Athanasios Kottas, Rajarshi Guhaniyogi and Bruno Sanso.