My research interests revolve around all aspects of Machine Learning: theory, algorithms, and applications.

Currently I focus on the foundations of privacy-preserving data analysis, including Differential Privacy and Private Multi-Party Machine Learning.

In the past I worked on scalable spectral algorithms for learning latent-variable models inspired by Language Theory and Dynamical Systems, and motivated by applications in Natural Language Processing and Reinforcement Learning.