My research focuses on efficiency problems of genetic algorithms and data
mining. My data mining interests include machine learning from labeled and
unlabeled data, learning from streaming data from nonstationary sources,
anomaly detection, feature subset selection, implementing efficient software,
and applying all these things to solve real problems. On evolutionary
algorithms, I am interested on efficiency problems in general. My dissertation
was on the parallelization of genetic algorithms, but I am interested on all
aspects of efficiently optimizing complex high-dimensional problems.
My vita (pdf)
and my publications
page have more details about me and my work.
