I graduated with my Ph.D. in Statistics from Iowa State University in December 2008 and started at St. Lawrence in January 2009. My interests are in Bayesian statistical methods and statistics education. My research comes from a problem I encountered while I spent time at Los Alamos National Laboratory, in Los Alamos, NM. It is often necessary for them to assess the reliability of complex systems (think missiles or any other large system with many smaller components/pieces). The most direct way to do this is to perform many tests of the entire systems. For many reasons this may not be feasible, so they have methodology that allows them to do assess the reliability of a system by testing the various components in that system. After the initial reliability assessments, they often get the opportunity (more money) to collect additional data and must decide which system components will give them the most new information about the reliability of the system. Their current strategy for doing this is extremely time-consuming and computationally intensive. In my research I have a developed a new strategy to reduce the computational burden and make this decision more quickly.