I am currently a Lane fellow in the Lane Center of Computational Biology at Carnegie Mellon University, working with Eric P. Xing. I received a Ph.D. in Computer Science and an M.A. in Statistics from UC Berkeley under the advising of Michael I. Jordan and Yun S. Song.
In broad terms, I am interested in problems that arise when working with large-scale, high-dimensional and complex structured data; examples that I have worked with include social networks, genomic sequences, biological pathways and gene expressions. My interest in analyzing these new data types is two-fold: first, develop scalable statistical models and efficient optimization algorithms for discovering and understanding hidden structures from complex data; second, improve interpretation and prediction of data by taking advantage of their inherent structures. Specifically, my current/recent focuses are: 1) latent space inference for large-scale networks, 2) high-dimensional nonparametric inference under structured sparsity, 3) applications in computational biology, statistical genetics and social systems.
In the past, I worked on the development of a new graphical model based on coalescent processes for estimation of gene conversion rates and mean conversion tract lengths, and a new model selection criterion for mutagenetic trees mixture models.