ml, data, software
My research applied theory in signal processing and machine learning to develop techniques for adaptive signal acquisition which can cope with measurement constraints. The goal of this work is to use structured data models to enable higher quality inference and prediction with less labeled data in diverse applications, e.g., imaging, targeted advertising, and recommendation systems.
My interests include: statistical signal processing, machine learning, active learning, randomized algorithms, compressed sensing, experimental design, recommendation systems, and collaborative filtering.
Before Georgia Tech, I attended the The Cooper Union for the Advancement of Science and Art where I received the Bachelor of Engineering degree.