If you are a prospective student who wants to work with me, click here; if you are a current student who wants to work with me, drop me an email. 

My research spans theoretical and applied machine learning, with a focus but is not limited to 

• learning (latent variable) probabilistic graphical models in high dimensions

• designing scalable and distributed spectral methods with guarantees

• efficient non-convex optimization with convergence guarantees, especially on tensor decomposition

• machine learning in social networks, natural language processing, computer vision, neuroscience, healthcare analytics and computational biology

    Keywords: machine learning, high-dimensional statistics, unsupervised learning, non-convex optimization, spectral methods, latent variable graphical model