I am a third-year Ph.D. candidate pursuing Neuroengineering under the supervision of Dr. Jose C. Principe. My doctoral research involves: (a) designing generative models that capture transient phasic events observed in electrophysiological recordings from the brain (EEG, MEG, ECoG, etc.) (b) developing a robust feature space from the properties of the identified transient events for an accurate prediction of subject intent and (c) studying the adaptive local communications between neural populations to construct functional connectivity maps in behaving animals.
My work heavily derives from the fields of machine learning, statistical signal processing, and information-theoretic learning. Additionally, I have also worked on different neural network frameworks and optimization models with application to computer vision and time series problems via coursework and academic projects.