Le Song is an Associate Professor in the Department of Computational Science and Engineering, College of Computing, and an Associate Director of the Center for Machine Learning, Georgia Institute of Technology. Le is also working with Ant Financial AI Department on risk management, security and finance related problems. He received his Ph.D. in Machine Learning from University of Sydney and NICTA in 2008, and then conducted his post-doctoral research in the Department of Machine Learning, Carnegie Mellon University, between 2008 and 2011. Before he joined Georgia Institute of Technology in 2011, he was a research scientist at Google briefly. His principal research direction is machine learning, especially nonlinear models, such as kernel methods and deep learning, and probabilistic graphical models for large scale and complex problems, arising from artificial intelligence, network analysis and other interdisciplinary domains. He is the recipient of the Recsys '16 Deep Learning Workshop Best Paper Award, AISTATS '16 Best Student Paper Award, IPDPS '15 Best Paper Award, NSF CAREER Award '14, NIPS '13 Outstanding Paper Award, and ICML '10 Best Paper Award. He has also served as the area chair or senior program committee for many leading machine learning and AI conferences such as ICML, NIPS, AISTATS, AAAI and IJCAI. He is also the action editor for JMLR, and associate editor for IEEE PAMI.