Assistant Professor of Neurology and Biomedical Engineering
- 2013, Doctoral Degree, Electrical Engineering, Yale University
- 2007, Bachelor's Degree, Mathematics and Polish Literature, University of Chicago
Dominique Duncan is an assistant professor of Neurology at the USC Stevens Neuroimaging and Informatics Institute in the Laboratory of Neuro Imaging (LONI). Dr. Duncan’s background spans mathematics, engineering, and neuroscience. She double majored in Mathematics and Polish Literature as an undergraduate at the University of Chicago and minored in Computational Neuroscience. She earned her PhD in Electrical Engineering at Yale University. In her PhD thesis, she analyzed intracranial EEG data using nonlinear factor analysis to identify preseizure states of epilepsy patients. After receiving her PhD, she was a professor of Mathematics at Sichuan University in Chengdu, China for a summer program for undergraduate students. She then took a postdoctoral position in Neurology at the Stanford University School of Medicine as well as one in Mathematics at UC Davis, where she developed an algorithm based on diffusion maps to classify Alzheimer’s patients using MRI. She has built international, multidisciplinary collaborations and developed novel analytic tools to analyze multimodal data, including imaging and electrophysiology. Her interests lie at the intersection of data analysis, signal processing, and machine learning, particularly in the areas of traumatic brain injury and epilepsy. By creating large-scale data repositories and linking them with visualization and analytic tools, for both neuroimaging and electrophysiology data as well as multimodal data of COVID-19 patients, she aims to encourage collaboration across multiple fields. Dr. Duncan also uses virtual reality to optimize the process of analyzing neuroimaging data and to improve neuroscience education among K-12 students.