Spring 2015 Seminar Series
Dr. Alberto Cano
University of Cordoba, Spain
Title: Evolutionary Mining in Large Databases
Abstract: The volume of data to analyze, stored in large databases is a challenging task for
data mining algorithms, including those based on evolutionary computation. This presentation
discusses and analyzes how data size and its characteristics affect the performance, accuracy
and scalability of algorithms. Classifiers based on evolutionary computation are introduced to
show the process of learning classification rules and their application to an educational data
mining problem. Efficient and scalable solutions to classification problems based on massively
parallel computing in graphic processing units (GPUs) are presented. Significant speedups are
achieved when distributing the process into multiple GPU devices, which allows mining in very
large databases within acceptable time.
Biography : Alberto Cano received the Ph.D. degree in Computer Science from the University
of Granada in 2014 and the MS degree in Soft Computing in 2011, from the same university. He
also received the MS degree in Intelligent Systems from the University of Cordoba in 2013 and
the BS degree in Computer Science in 2010. His research is currently funded by the Spanish
Ministry of Education. He is member of the Knowledge Discovery and Intelligent Systems group
and his research is focused on databases, soft computing, parallel computing and GPU
computing. He has published 12 journal articles, 2 book chapters and 9 conference papers. In
addition, he has published 15 papers on teaching practices and pedagogical innovation.
When: 12:00pm-1:00pm, Monday, March 16, 2015
Where: Room E2221, School of Engineering-East Hall, Monroe Campus