His research in machine learning focuses on extracting latent knowledge from free form text, knowledge bases, and social networks using unsupervised feature learning (deep learning). Particularly, in his thesis, he focuses on applying language modeling to enable massive multilingual natural language applications. His aim is to build intelligent systems with minimal human effort that support all human languages. He believes that efficient algorithms for learning knowledge representation are at the core of such goal.