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April 9, 2021 at 14:30

Teams Seminar


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Prof. Giuseppe Maulucci

Dipartimento di Neuroscienze

Università Cattolica del Sacro Cuore

Rome, Italy

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Maulucci Giuseppe was born in Rome in 1978. He attended the university of « La Sapienza » in Rome, where he graduated in biophysics in 2003. He obtained his PhD in physics from the University of « Rome 3 » in 2008 and in 2009 he had a postdoctoral research-fellow at the Institute of Physics and at the center of light and electron microscopy of the Università Cattolica del Sacro Cuore (UCSC). He acquired experience with numerous experimental techniques, such as the elastic and quasi elastic light scattering, the atomic force microscopy, scanning and transmission electron microscopy and confocal and multiphoton microscopy. In 2005 he got a specialization in the use of microscopy techniques at the University of Florence ( Course on “Innovative Microscopy for Biotechnology”), and at the University of Genoa(course “Principles of Fluorescence techniques “). In 2008 and 2011 he received three research assignments at European Sinchrothron Radiation Facility (ESRF), Grenoble (FRA) and at Laboratoire Léon Brillouin CEA de Saclay Gif-sur-Yvette Cedex (FRA) and at synchrotron SOLEIL Gif-sur-Yvette Cedex (FRA). In 2011 he became Assistant professor in applied physics at UCSC, Rome. In 2014 he was a research fellow at the Pharmacology department of the Hebrew university of Jerusalem following a research project about membrane biophysical properties and intracellular transfer of insulin-containing granules in beta–cells. From 2018 he is associate professor at UCSC, sector 02/B3.
He is Author of 86 Publications on peer reviewed journal, H-Index is 31, Total Citations : 2434 (Scopus, Author ID:8414754400). He is member of several international associations (SIF,SIPBA, Biophysical Society), editor and reviewer for peer-reviewed scientific journal and recipient of national and international grants (MIUR; Ministero Salute, regione Lazio, FP7, EASD).
Research activity is focused on the development of Machine learning and AI-aided imaging and spectroscopic techniques for the study of metabolism and metabolic networks, with application on diagnostic and decision support system for diabetes Care. Machine Learning assisted methods to investigate glucose metabolism, lipid metabolism, redox homeostasis and autophagic processes with submicrometric resolution were developed to improve the treatment of metabolical disorders by optimizing the pre-clinical and clinical tests of new medication.


9 April 2021
14:30 - 16:30