Michele De Filippo De Grazia

Personal Page of Michele De Filippo De Grazia

Michele De Filippo De Grazia


Research Fellow

Department of General Psychology
University Of Padova
via Venezia 12/2
35131 Padova (Italy)

tel : +39 049 827 6941
fax: +39 049 827 6600
e-mail: michele.defilippodegrazia(at)unipd.it
office: room 008 (ground floor), Building Psico2


Research Interests
My research interests are focused on Machine Learning techniques like neural networks and SVM algorithms to develop intelligent systems to, for example, fault detection and diagnosis of HVAC systems, in time series analysis and for rehabilitation videogame.
During my research I am also involved in the development of computational models (as deep networks) for cognitive processes. In particolar a model that mimic the sensorimotor transformations occuring in PPC brain area for investigate the space representation mechanisms and the visual/postural information integration methods.
These complex cognitive models have a high computational cost so I developed a parallel computing paradigm to reduce the computer time of unsupervised learning in deep networks, based on distributing training data among multiple computational nodes in a cluster throught Message Passing Interface (MPI) a standardized and portable message-passing system.

Laurea (M.Sc.), Computer Science, University of Padova (2008)

Representative publications

  • Space Coding for Sensorimotor Transformations can emerge through Unsupervised Learning, M. De Filippo De Grazia, S. Cutini, M. Lisi, M. Zorzi, Cognitive Processing, 13(Suppl 1):141-146 (2012)
  • Parallelization of Deep Networks, M. De Filippo De Grazia, I. Stoianov, M. Zorzi, Proceedings of ESANN 2012, 621-626 (2012 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning) (2012)
  • Application of the Preference Learning Model to a Human Resources Selection Task, F.Aiolli, M. De Filippo De Grazia, A. Sperduti, Proceedings of the IEEE CIDM 2009, 203-210 (2009 IEEE Symposium on Computational Intelligence and Data Mining) (2009)