Tartaglione

Enzo Tartaglione received a joint Master’s degree in Electronic Engineering from: Politecnico di Torino, University of Illinois at Chicago and Politecnico di Milano in 2015. He received the Alta Scuola Politecnica diploma in 2016. In 2019, he defended his PhD thesis at Politecnico di Torino, on the topic “From Statistical Physics to Deep Neural Network Algorithms”. From 2019 to 2021, he held a postdoctoral position at the University of Turin, working on the European project  DeepHealth. His research topics include neural networks pruning, compression, quantization, regularization, deep learning applied to medical image processing, data and model debiasing, privacy preservation.

Keywords: neural networks pruning, compression, quantization, regularization, deep learning, model debiasing, privacy preservation

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