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Danilo Benozzo is a PhD student in Computer Science at the doctoral school in Information and Communication Technology (University of Trento, Italy). He received his master's degree in bioengineering from the University of Padova (Italy) defending the thesis with title “Deconvolution algorithm optimization in DSC-MRI”. His research activity is in the field of neuroinformatics focusing in particular on the analysis of functional brain data using machine learning algorithms. Nowadays, neuroscience is showing interest in the application of machine learning methods to analyze neuroimaging data and an example of this trend is brain decoding. Brain decoding aims to study stimulus-related brain activity in order to establish a link between activation patterns and related external stimuli. His research is mainly focused on some brain connectivity measures and the study of interactions between brain regions by means of Bayesian nonparametric relational model.
- Benozzo D., Peruzzo D., Castellaro M., Pillonetto G. and Bertoldo A. “Optimized Non-linear Stochastic Regularization for DSC-MRI”. Presented at the ESMRMB 29th Annual Scientific Meeting. Lisbon, Portugal, 4-6 October 2012.
- Peruzzo D., Benozzo D., Pillonetto G. and Bertoldo A. “Fast NSR: an optimized Non-linear Stochastic deconvolution for large data set and clinical analyses”. Presented at the ISMRM 21st Scientific Meeting and Exhibition. Utah, USA, 20-26 April 2013.
- Olivetti E., Benozzo D., Mostaka Kia S., Ellero M. and Hartmann T. “The Kernel Two-Sample Test vs. Brain Decodinig”. Presented at the 3rd International Workshop on Pattern Recognition in Neuroimaging. Philadelphia PA, USA, June 22-24 2013