My research interest is system identification and modeling of complex systems and data--both development of novel mathematical tools and algorithms and application to challenging problems. My graduate studies were in statistical signal processing, mathematical modeling, and computational neuroscience. My graduate work was a rigorous analysis of problems related to Granger causality, a set of statistical tools widely used in neuroscience. My early post-doc research at MGH was part of the DARPA Transform DBS project, analyzing, modeling, and decoding two behavioral tasks from multiple signal modalities, including local field potentials (LFP) and electrocorticography (ECoG). My most recent post-doc research has been developing methods for the analysis of sleep dynamics from electroencephalography (EEG).