This resume is current as of July 2011. -Mike
RESEARCH INTERESTS
My PhD research applies techniques from statistical machine learning (particularly hierarchical Bayesian models and nonparametric extensions) to create automated methods for extracting meaningful information from multimedia. I study theoretical methods for efficient inference in graphical models (e.g. MCMC sampling, variational methods) as well as practical ways to apply these methods to real-world data such as video clips or text documents.
Michael C. Hughes
RESEARCH INTERESTS
My PhD research applies techniques from statistical machine learning (particularly hierarchical Bayesian models and nonparametric extensions) to create automated methods for extracting meaningful information from multimedia. I study theoretical methods for efficient inference in graphical models (e.g. MCMC sampling, variational methods) as well as practical ways to apply these methods to real-world data such as video clips or text documents.
BROWN CAMPUS * Box 1910, CS Dept. * 115 Waterman St * Providence, RI 02906 mike@michaelchughes.com |