Prem Melville received a Ph.D. in Computer Science at the University of Texas at Austin. His research interests lie in Machine Learning and Data Mining. More specifically, he has worked on ensemble methods, active learning, active feature-value acquisition, recommender systems and class probability estimation. His Ph.D. thesis concentrated on building diverse ensembles of classifiers leading to more accurate predictive models than existing methods, with reduced supervision, which translates to lower costs of data acquisition.
Prem joined the Data Analytics Research Group as a Research Staff Member in February 2006. His current research focuses on anomaly detection and data modeling for improved sales performance.
