Multimodal Signal Analysis and Data Fusion for Post-traumatic Epilepsy Prediction is a project funded by NIH. In collaboration with researchers at USC Medical School, we are using machine learning techniques to discover features from multimodal data such as EEG, fMRI, DTI, and blood chemistry, in order to build models that can predict if a traumatic brain injury (TBI) patient is susceptible to epileptogenesis – emergence of epilepsy following TBI.