Stefano Fasciani
Associate Professor

Norwegian version of this page
Phone
+47-22844146
Room
320
Username
Visiting address
Sem Sælands vei 2
ZEB building
0371 Oslo
Norway
Postal address
P.O. Box 1017
Blindern
0315 Oslo
Norway
Short Bio: Stefano Fasciani has an academic background in electronic engineering and professional experience in the semiconductor industry and in the club scene. His research and personal interest are focused on technologies for sonic arts, including sound and music computing, sound synthesis and analysis, applied machine learning, human computer interaction, networked music performances, digital signal processing, and real-time embedded systems.
Academic interests
- Music Technology
- Sound and Music Computing
- Sound Synthesis
- Networked Music Performances
- Computer Music
- Machine Learning
- Digital Signal Processing
- Embedded Systems
- Computing Architectures
Administration
Teaching
- MCT4052 Music and Machine Learning
- MCT4054 Interactive Music Systems
- MCT4033 Applied MCT Project
- MCT4001 Introduction to Music, Communication and Technology
- MCT4091 Master's Thesis in Music, Communication and Technology
Background and Appointments
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2015-2019 Assistant Professor, Faculty of Engineering and Information Systems, University of Wollongong, Dubai, UAE
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2015-2015 Postdoc Research Fellow, DSP Lab, School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore
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2011-2014 Ph.D. Integrative Sciences and Engineering, National University of Singapore
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2010-2011 Research Fellow, Multimodal Analysis Lab, Interactive and Digital Media Institute, National University of Singapore, Singapore
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2006-2010 DSP Application Engineer, Atmel Corporation, Advanced DSP Center, Rome, Italy
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2004-2006 M.Sc. Electronic Engineering, University of Rome Tor Vergata, Italy
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2000-2003 B.Sc. Electronic Engineering, University of Rome Tor Vergata, Italy
Publications
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Copiaco, Abigail; Ritz, Christian; Fasciani, Stefano & AbdulAziz, Nidhal (2022). Development of a Synthetic Database for Compact Neural Network Classification of Acoustic Scenes in Dementia Care Environments. In APSIPA, . (Eds.), 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE Signal Processing Society. ISSN 9789881476890. p. 1202–1209. Full text in Research Archive
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Fasciani, Stefano & Goode, Jackson Montgomery (2021). 20 NIMEs: Twenty Years of New Interfaces for Musical Expression. In Dannenberg, Roger & Xiao, Xiao (Ed.), Proceedings of the International Conference on New Interfaces for Musical Expression. The International Conference on New Interfaces for Musical Expression. ISSN 2220-4792. doi: https%3A/doi.org/10.21428/92fbeb44.b368bcd5. Full text in Research Archive
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Copiaco, Abigail; Ritz, Christian; Abdulaziz, Nidhal & Fasciani, Stefano (2021). A Study of Features and Deep Neural Network Architectures and Hyper-Parameters for Domestic Audio Classification. Applied Sciences. ISSN 2076-3417. 11(11). doi: 10.3390/app11114880.
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Copiaco, Abigail; Ritz, Christian; Fasciani, Stefano & AbdulAziz, Nidhal (2021). Identifying Sound Source Node Locations Using Neural Networks Trained with Phasograms. Proceedings of IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). ISSN 2641-5542. doi: 10.1109/ISSPIT51521.2020.9408643.
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Copiaco, Abigail; Ritz, Christian; Fasciani, Stefano & Abdulaziz, Nidhal (2020). An Application for Dementia Patient Monitoring with Sound Level Assessment Tool. In IEEE, . (Eds.), 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS). IEEE. ISSN 978-1-7281-8998-7.
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Jensenius, Alexander Refsum & Fasciani, Stefano (2021). University of Oslo - RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion. Proceedings of the SMC Conferences. ISSN 2518-3672. 2021-.
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Fasciani, Stefano & Jensenius, Alexander Refsum (2021). Sound and Music Computing at the University of Oslo. Show summary
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Jenssen, Ariadne Loinsworth; Monstad, Lars; Gonzalez Munoz, Sofia; Fasciani, Stefano & Jensenius, Alexander Refsum (2021). Kan kunstig intelligens erstatte en artist?
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Fasciani, Stefano (2021). Back-To-Net – A system for collaborative DJ set over the Internet.
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Jensenius, Alexander Refsum; Erdem, Cagri; Kwak, Dongho Daniel; Rahman, Habibur; Glette, Kyrre & Krzyzaniak, Michael Joseph [Show all 7 contributors for this article] (2020). Strings On-Line. Show summary
Published May 6, 2019 3:32 PM
- Last modified Nov. 17, 2021 10:14 AM