At the University of Chicago, I conduct research in computer-aided diagnosis of breast and ovarian cancer, focusing on the modalities of dynamic contrast-enhanced magnetic resonance imaging and ultrasound. My primary areas of interest are in artificial intelligence and radiomics across the imaging and classification pipeline, from image acquisition to performance evaluation and data harmonization. A particular area of interest for me is the development and evaluation of patient-level medical imaging AI output methodologies and technologies. I also conduct research and collaborate in MIDRC, the Medical Imaging and Data Resource Center. Within MIDRC I work on methods of task-based distributions, interoperability between data enclaves, and monitoring and studying the diversity and representativeness of the MIDRC data commons to foster research in AI and health disparities. Additionally, I have over a decade of experience in teaching and working with trainees and in research collaborations.