Assistant Professor of Computer Science, California State University, Fresno
We propose to develop an integrated network-centric approach to identify brain anomalies (Schizophrenia, Insomnia, Epilepsy, Autism, and Alcoholism) using innovative, non-invasive approaches involving electroencephalogram (EEG) data and imagery, complex network analysis, and predictive analytics. Such a novel and original perspective as brain modeling is crucial and made possible with the advent of cloud computing platforms and big data algorithms. The closely intertwined research activities include: (1) designing a modular framework for detection of healthy brains; (2) developing prediction models and deep learning architectures to classify anomaly among brain imagery; and (3) conducting a network analysis of brain data.