Mario R. Guarracino

Mario Guarracino is researcher at High Performance Computing and Networking Institute of the Italian National Research Council. He received a PhD in Mathematics an Ms in Applied Mathematics from University of Naples Federico II. His postdoctoral training from National Research Council focused on low cost high performance architectures for scientific computing. He has been collaborating with Center for Applied Optimization at University of Florida since 2005. He has taught various graduate and undergraduate courses in computer science, statistics and mathematics.

His research interests include machine learning methods for computational biology and planning and development of high performance computational components for parallel and distributed problem solving environments. He is author of publications in the field of high performance scientific computing, computational biology and machine learning.

Publications

Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems
Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems
Petraq Papajorgji, Alaine Margarete Guimarães, Mario R. Guarracino. © 2013. 252 pages.
Many factors can impact large-scale enterprise management systems, and maintaining these systems can be a complicated and challenging process. Therefore, businesses can benefit...
Application of Support Vector Machines to Melissopalynological Data for Honey Classification
Application of Support Vector Machines to Melissopalynological Data for Honey Classification
Giovanna Aronne, Veronica De Micco, Mario R. Guarracino. © 2012. 10 pages.
In this paper, the authors address the problem of the discrimination of geographical origin and the selection of marker species of honeys using Support Vector Machines and...
Application of Support Vector Machines to Melissopalynological Data for Honey Classification
Application of Support Vector Machines to Melissopalynological Data for Honey Classification
Giovanna Aronne, Veronica De Micco, Mario R. Guarracino. © 2010. 10 pages.
In this paper, the authors address the problem of the discrimination of geographical origin and the selection of marker species of honeys using Support Vector Machines and...