Codes & Data
ML Group

Le Song

Assistant Professor

Computational Science and Engineering
College of Computing
Georgia Institute of Technology

1340 Klaus Building
266 Ferst Drive
Atlanta, GA 30332, USA



I am heading the Machine Learning Group at Georgia Institute of Technology. I conduct research in the development of machine learning methodology, and the applications of machine learning to interdisciplinary problems. I am fascinated by the prospect of intelligent systems which can learn from massive volumes of complex, uncertain and high dimensional data, and reveal trends and patterns too subtle for humans to detect. Problems I have addressed are as diverse as finding disease markers from thousands of candidate genes, modeling and predicting nonlinear spatial-temporal dynamics in sensor time-series, and estimating and analyzing social and biological networks. Data arising from these applications are often characterized by complex statistical features (eg. multi-modality, skewness), and long-range and hierarchical dependencies among the involved variables. More specifically, my current projects involve


Selected Recent Publications

Brief Biography

I studied computer science at the South China University of Technology, Guangzhou, China in 1998. After I obtained my Bachelor's degree in 2002, I traveled to Sydney, Australia. In 2004 I received my Master's degree, and in 2008 my Doctoral degree in computer science at the University of Sydney, Australia. I was also a PhD. student with the Statistical Machine Learning Program at NICTA. My thesis advisor is Alex Smola. Since Summer 2008, I was a Lane postdoc fellow at Carnegie Mellon Univeristy, working on machine learning and computational biology projects with Eric Xing, Carlos Guestrin, Geoff Gordon and Jeff Schneider. Right before I came to Georgia Tech, I spent some time as a research scientist in Fernando Pereira's group at Google Research.

Curriculum Vitae