My research interests lie on developing pattern recognition techniques for multiple modalities of brain signal processing, from neurophysiological signals such as electroencephalograms (EEGs) and electrocorticograms (ECoGs) to neuroimaging data such as functional magnetic resonance imaging (fMRI). Specifically, my technical research focuses on developing new computational techniques/tools to optimally extract spatial and temporal characteristics of multidimensional time series data. My research applications include the study of brain diseases, cognitive functions, and human performance. In the past 11 years, my expertise in signal processing and brain network (connectivity) modeling has been proven beneficial and innovative in the brain research.
In my lab, I have cultivated strong collaborative relationships with diverse groups of scientists, and led several multidisciplinary teams in investigating emerging neural engineering problems such as predicting epileptic seizures, identifying a surgically-targeted subcortical structure in Parkinson's deep brain stimulation candidates, localizing neurosurgical target in epilepsy, and predicting human performance and cognitive load from brain activity. My ultimate goal is to accelerate from the innovation in brain pattern analysis to the translation of the proposed research program into clinical practice.