Ankur Parikh

Ankur Parikh is a 4th year PhD student at Carnegie Mellon University and is advised by Prof. Eric Xing. His research interests are in spectral and kernel methods for probabilistic graphical models as well as computational biology. He is fortunate to be funded by an NSF graduate research fellowship.

Le Song

Dr. Le Song is an assistant professor at College of Computing, Georgia Institute of Technology since Fall 2011. He received his Ph.D. in machine learning from University of Sydney and National ICT Australia in 2008. He also worked as a postdoctoral fellow at Carnegie Mellon University in 2008-2011 and a research scientist at Google Research in 2011 respectively. His research interests are nonparametric kernel methods, probabilistic graphical models, time series and network analysis, and applications of machine learning to texts, images, networks, computational biology and information rich social media.

Eric Xing

Dr. Eric Xing is an associate professor in the School of Computer Science at Carnegie Mellon University. His principal research interests lie in the development of machine learning and statistical methodology; especially for solving problems involving automated learning, reasoning, and decision-making in high-dimensional and dynamic possible worlds; and for building quantitative models and predictive understandings of biological systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. His current work involves, 1) foundations of statistical learning, including theory and algorithms for estimating time/space varying-coefficient models, sparse structured input/output models, and nonparametric Bayesian models; 2) computational and statistical analysis of gene regulation, genetic variation, and disease associations; and 3) application of statistical learning in social networks, data mining, vision. Professor Xing has published over 150 peer-reviewed papers, and is an associate editor of the Journal of the American Statistical Association, Annals of Applied Statistics, the IEEE Transactions of Pattern Analysis and Machine Intelligence, the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning journal. He is a recipient of the NSF Career Award, the Alfred P. Sloan Research Fellowship in Computer Science, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Faculty Award.