James L. Carmon Scholarship Award 2009
Ming-Hung Kao, a doctoral candidate in statistics, developed sophisticated software that provides optimal experimental designs for event-related functional magnetic resonance imaging (fMRI) studies. This brain-mapping technique, used both in medical practice and scientific research, is one of the most critical tools in neuroscience. Yet its images are expensive, and the signal-to-noise ratio in resulting experimental data is poor. Kao has proposed an efficient knowledge-based algorithm for developing a research design that achieves statistical goals and that, in some sense, does so in the most efficient way. His approach also fulfills the customization requirements for an event-related fMRI study that involves one or more stimulus types. His research won a student-paper award in the Statistical Computing/Statistical Graphics section of the 2008 Joint Statistical Meetings in Denver, Colorado, and a related paper has been accepted for publication in NeuroImage, the leading journal in the field.