As a postdoc in the Penn Statistics in Imaging and Visualization Endeavor (PennSIVE) Center of Excellence, I work on the development and application of statistical and machine learning methods for studies of neuropsychiatric disorders, with a specific focus on neuroimaging data. My postdoc mentors, Drs. Kristin Linn and Russell Shinohara, and I recently developed a method for harmonizing longitudinal neuroimaging data collected on different MRI scanners, which can introduce unwanted "scanner effects." My PhD dissertation work at University of Pittsburgh used a novel structured, sparse, penalized regression method to predict clinical and behavioral data, such as assessment scores or age, from brain images. I am also interested in developing computational methods to help refine psychiatric diagnostic categories using diverse data modalities, as current systems result in diagnoses that are often heterogeneous and have high rates of comorbidity.