Marco Lorenzi
About Marco Lorenzi
Marco Lorenzi is a Research Scientist with a background in Mathematics and Computer Science, specializing in Medical Imaging. He has worked at notable institutions including Inria and University College London, and has authored numerous publications in his field.
Current Role at Inria
Marco Lorenzi serves as a Research Scientist at Inria, a position he has held since 2016. He is based in the Sophia Antipolis facility, where he focuses on advancing research in his field. His work involves applying his expertise in medical imaging and computer science to develop innovative solutions and methodologies.
Previous Experience at Inria
Prior to his current role, Marco Lorenzi worked at Inria as a Postdoctoral Researcher from 2012 to 2014. During this time, he contributed to various research projects and collaborated with other experts in the field. His experience at Inria laid the foundation for his ongoing research in medical imaging.
Educational Background
Marco Lorenzi completed his Master's degree in Mathematics at Università degli Studi di Torino from 2002 to 2007. He furthered his education by pursuing a Doctor of Philosophy (PhD) in Computer Science with a focus on Medical Imaging at Université Côte d'Azur from 2009 to 2012. His academic background equips him with a strong foundation in both theoretical and applied aspects of his research.
Research Experience at University College London
From 2014 to 2016, Marco Lorenzi worked as a Research Associate at University College London. He was part of the Translational Imaging Group, where he engaged in research that bridged the gap between scientific discovery and clinical application. His role involved collaboration with multidisciplinary teams to enhance imaging techniques.
Consulting and Research Assistant Roles
Before his tenure at University College London, Marco Lorenzi spent three years as a research assistant and statistical consultant at the Research Hospital IRCCS Fatebenefratelli in Brescia, Italy. This role allowed him to apply his statistical knowledge in a clinical setting, contributing to various research initiatives.