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Matteo Spallanzani

I received my PhD in applied mathematics in February 2020 from the University of Modena and Reggio Emilia (UniMoRe), Italy, with a thesis on "A framework for the analysis of machine learning systems". I have been working on data science and machine learning for five years, both in academia and industry (Tetra Pak, Maserati, Advertima).


I am interested in everything that can help me finding and understanding the patterns hidden in our world. Since I found out that boosting statistical models with parallel computers can be pretty efficient at this task, I have made it my job to understand how machine learning systems work and how to apply them to real-world problems. My research interests lie at the intersection of mathematical analysis, stochastic optimisation, algorithms, and parallel programming.

At IIS, I am working on quantised neural networks (QNNs): applying data science techniques to know how good networks look like, developing new algorithms to improve their learning process, and crafting tools to deploy them on resource-constrained computing platforms.

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