Research interests:

My research interests are mainly nonparametric methods for machine learning. This includes kernel methods and exponential families, especially support vector machines, conditional random fields, and nonparametric Bayesian methods. I am also interested in probabilistic modeling with graphical models and efficient inference. Using undirected graphical models and kernel representation of distributions, I study the independence tests for structured data which has many applications to unsupervised learning. In practice, large scale optimization techniques are required and I am particularly interested in first order methods such as conditional gradient methods.

Bio:

I am currently a Researcher at the Machine Learning Group of National ICT Australia (NICTA). From April 2010 to September 2012, I was a post-doc working with Prof Dale Schuurmans at the Department of Computing Science, University of Alberta. From March 2006 to October 2009, I was a NICTA-endorsed PhD student of the School of Computer Science, Australian National University (ANU), where I was also affiliated with the Statistical Machine Learning Program of NICTA. I visited Prof SVN Vishwanathan at the Department of Statistics at Purdue University from February 2009 to March 2010. From January 2004 to March 2006, I pursued my Master's degree (by research) at the Department of Computer Science, National University of Singapore (NUS). I received my B.E. Degree from the Department of Computer Science and Engineering at Shanghai Jiao Tong University in July 2003.

Research opportunities with Dr Xinhua ZHANG

• Large Scale Optimization for Sparse Modeling
• Convex Relaxation for Latent Models