The proposed program is devoted to the application of probability and statistics to problems in three areas: the genome sciences, networks and financial engineering. These application areas are all associated with complex systems, and strategies for system analysis will serve as an organizing principle for the program. (By complex systems we mean systems with a very large number of interacting parts such that the interactions are nonlinear in the sense that we cannot predict the behavior of the system simply by understanding the behavior of the component parts.) Furthermore, these areas share the common feature that they are systems for which a huge amount of data is available.Mathematical models developed for these systems must be informed by this data, if they are to provide a basis for scientific understanding of the systems and for critical decision-making about them. The mathematical and statistical foundations of this program will include stochastic modeling and simulation, statistics, and massive data set analysis, as well as dynamical systems, network and graph theory, optimization, control, design of computer and physical experiments, and statistical visualization. The program will be particularly appropriate for probability/statistics postdocs and long-term participants with some background in at least one of the three major areas of application and an interest in developing the integration tools that will provide them with an entrée into modeling/data integration issues in the other areas. There will be extensive tutorials in the application areas.
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Last modified on October 06, 2011