My research focuses in finding hidden patterns in data, which is embedded in high dimensions but is intrinsically low dimensional. Some of the tools I use in my work include clustering, topological data analysis, probabilistic models, and dimension reduction methods. In the past, I’ve applied my research to segmentation of natural and material images. Currently, I am involved in a collaborative project that seeks to develop mathematical tools to help predict Obstructive Sleep Apnea (OSA) in children.