Stefano Fasciani

Associate Professor

Norwegian version of this page

Email stefano.fasciani@imv.uio.no

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

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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

Leader of Master's programme in Music, Communication and Technology

Teaching

Background and Appointments

2015-2019 Assistant Professor, Faculty of Engineering and Information Systems, University of Wollongong, Dubai, UAE
2015-2015 Postdoc Research Fellow, DSP Lab, School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore
2011-2014 Ph.D. Integrative Sciences and Engineering, National University of Singapore
2010-2011 Research Fellow, Multimodal Analysis Lab, Interactive and Digital Media Institute, National University of Singapore, Singapore
2006-2010 DSP Application Engineer, Atmel Corporation, Advanced DSP Center, Rome, Italy
2004-2006 M.Sc. Electronic Engineering, University of Rome Tor Vergata, Italy
2000-2003 B.Sc. Electronic Engineering, University of Rome Tor Vergata, Italy

Tags: Music Technology, Sound and Music Computing, Machine Learning, Digital Signal Processing, Embedded Systems, Computing Architectures, Computer Music

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
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
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.
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.
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.

View all works in Cristin

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-.
Fasciani, Stefano & Jensenius, Alexander Refsum (2021). Sound and Music Computing at the University of Oslo. Show summary
A presentation of labs and studios at the Department of Musicology and RITMO Centre for Interdisciplinary Studies in Rhythm, Time, and Motion at the University of Oslo.
Jenssen, Ariadne Loinsworth; Monstad, Lars; Gonzalez Munoz, Sofia; Fasciani, Stefano & Jensenius, Alexander Refsum (2021). Kan kunstig intelligens erstatte en artist?
Fasciani, Stefano (2021). Back-To-Net – A system for collaborative DJ set over the Internet.
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
An interactive art installation presented during the International Conference on New Interfaces for Musical Expression (NIME) 2020.