Livio Saracino
About Livio Saracino
Livio Saracino is a Research Engineer with expertise in advanced digital signal processing and psychoacoustics. He holds degrees from the University of Exeter, Università degli Studi di Modena e Reggio Emilia, and Università di Bologna, and has experience in R&D, machine learning, and algorithm design.
Work at MUSIC Tribe
Livio Saracino has been employed as a Research Engineer since 2020. In this role, he contributes to the development of innovative audio technologies. His responsibilities include researching and implementing advanced digital signal processing (DSP) techniques and psychoacoustic models to enhance audio tools. His work is integral to the company's commitment to advancing audio technology.
Education and Expertise
Livio Saracino holds a Bachelor's Degree in Electronic and Telecommunication Engineering from Università degli Studi di Modena e Reggio Emilia, completed from 2011 to 2014. He furthered his education with a Master's Degree in Electronic, Electric and Telecommunication Engineering from Università di Bologna, which he obtained from 2014 to 2017. He also studied at the University of Exeter under the Erasmus program, focusing on Electrical, Electronics and Communications Engineering for one year in 2013-2014. His expertise lies in advanced DSP and psychoacoustics, as well as music information retrieval algorithms.
Background
Before joining MUSIC Tribe, Livio Saracino worked as a Junior Research Engineer from 2018 to 2020 in Manchester, UK. He has experience in signal and image processing, having worked at Cellply, a biomedical startup, in 2016. His background includes co-founding EasyPCR, a startup dedicated to developing DNA analysis tools, showcasing his interest in research and development of new technological solutions.
Achievements
Livio Saracino has made significant contributions to the field of audio technology through his work on smart audio tools as part of the R&D and machine learning team at Midas. His skills in algorithm design using programming languages such as C++, Python, and Git have enabled him to develop effective solutions in audio processing. His involvement in startups and research projects reflects his commitment to advancing technology in both audio and biomedical fields.