Giulia Pasquale was born in Genoa in 1988. She received the Bachelor's degree in Biomedical Engineering at the University of Genoa in 2010. Her thesis project consisted in the improvement of a recursive convolutional neural network for the extraction of binocular disparity information from the visual signal, implementing an algorithm for learning lateral interconnection weights of a Winner-Take-All layer. She got the Master's Degree in Bioengineering -curriculum Neuroengineering- at the same university in February 2013, working on the developement of a small CUDA-accelerated library for real-time visual feature coding and estimation through convolutional networks. During the period March-December 2013 she has been a research fellow at the Institute for Applied Mathematics and Information Technologies of the National Research Council in Genoa, where she worked on the parallelization of algorithms for the stochastic simulation of biological systems in the context of the InterOmics Flagship Project. She is currently a fellow-PhD at the iCub-Facility of the Italian Institute of Technology, working on deep learning methods for object recognition and their efficient parallel implementation for robotics applications.