Charles Sutton

I am delighted to announce the appointment of Dr. Charles Sutton to a SICSA lecturership in the School of Informatics.

Charles has been a postdoctoral researcher at the University of California, Berkeley, since 2007. His recent work has aimed at new statistical machine learning methods designed to aid the management of large-scale computer systems. In particular, he has developed methods for performance modeling that are rooted in machine learning, applying them to the control, visualization, and diagnosis of distributed Web applications. More generally, his research interests include machine learning, graphical models, approximate inference, structured prediction, natural language processing, and the application of machine learning methods to computer systems. Charles received his PhD from the University of Massachusetts Amherst in 2008. His thesis work concerned efficient training methods for conditional random fields, with applications in natural language processing.