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Bocconi University invests in machine learning with Riccardo Zecchina, a brain “not on the run”

Bocconi University invests in machine learning with Riccardo Zecchina, a brain “not on the run”

Riccardo Zecchina (pictured) has been engaged for years in frontier research in computer science, statistical physics, information theory and computational biology. He has received several international recognitions including the prestigious Lars Onsager Prize from the American Physical Society in 2016. He has also obtained several grants from the European Research Council (ERC), which awards European excellence in research on highly innovative projects.

“The distinguishing feature of my research activity – explains Zecchina, formerly at the Polytechnic University of Turin and currently a Professor at the Department of Decision Sciences at Bocconi University in Milan – has consisted in the identification of algorithmic counterparts of the advanced analytical techniques developed in the context of statistical physics of complex systems. This has led to novel distributed algorithms which have moved forward the boundaries of optimization and inference problems considered to be typically intractable”.

The researcher from Milan every day deals with the so-called ‘machine learning’, that is, the development of the ability of computers to learn automatically from the data that they process and make predictions of complex and ‘deep’ phenomena. It is known that managing ‘Big Data’, i.e. the large volume of raw data from which to extract significant information, is highly problematic and ‘machines’ have to be able to learn by themselves – certainly with the help of humans that feed them with new algorithms – how to generalize from examples and establish reliable causal connections.

“Today – continues the researcher – many examples of Artificial Intelligence are able not only to extract significant information from large amounts of data but also to perform some specialized tasks such as recognizing objects or playing chess sometimes more efficiently than humans. The real progress has been triggered by the combined development of novel technologies for data production and acquisition, of more powerful computer platforms and of novel machine learning algorithms, such as artificial deep neural networks inspired by human neural systems”.

Source Università Bocconi
Publication date 03/28/2017
Tag Physical Sciences and Engineering