Perry Samson

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The capacity to predict student success depends in part on our ability to understand “educationally purposeful” student behaviors and motivations and the relationship between behaviors and motivations and academic achievement. My research focuses on how to collect student behaviors germane to learning at a higher granularity and analyze the relationships between student performance and behaviors.

Ultimately this research is aimed at designing and constructing an “earlier warning system” wherein student guidance is quasi-automated and informed by motivation, background and behaviors and delivered within weeks of the beginning of classes.

Quentin Stout

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I primarily work on developing scalable parallel algorithms to solve large scientific problems. This has been done with teams from several different disciplines and application areas. I’m most concerned with algorithms emphasizing in-memory approaches. Another area of research has developed serial algorithms for nonparametric regression. This is a flexible form of regression that only assumes a general shape, such as upward, rather than a parametric form such as linear. It can be applied to a range of learning and classification problems, such as taxonomy trees. I also work some in adaptive learning, designing efficient sampling procedures.