Dr. Li’s research develops statistical machine learning algorithms for modeling and inference of complex-structured datasets with high dimensionality (e.g., 3D/4D images), multi-modality, and heterogeneity. The objectives of the methodological developments are to provide capacities for monitoring & change detection, diagnosis, and prediction & prognosis. The application domains mainly include health and medicine, focusing on medical image data analytics as well as fusion of images, genomics, and clinical records for personalized and precision medicine. Her research outcomes support clinical decision making for diagnosis, prognosis, and telemedicine for various conditions affecting the brain, such as brain cancer, post-traumatic headache & migraine, traumatic brain injury, Alzheimer’s disease, etc. Her research received Best Paper awards from various professional venues such as IISE Transactions, IISE Annual Conferences, INFORMS Data Mining and Decision Analytics, American Academy of Neurology, America Headache Society, etc. Her research has been funded by the NIH, NSF, DOD, and industries. She is an NSF CAREER Awardee.