Stefano Fasciani

Associate Professor
Image of Stefano Fasciani
Norwegian version of this page
Phone +47-22844146
Room 320
Username
Visiting address Sem Sælands vei 2A 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

  • Sound and Music Computing
  • Sound Synthesis
  • Networked Music Performances
  • Computer Music
  • Machine Learning
  • Digital Signal Processing
  • Embedded Systems
  • Computing Architectures

Leadership

Teaching

Teaching Portfolio

Supervised Students

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

Research and Education Projects

 

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

Publications

  • Simionato, Riccardo; Fasciani, Stefano & Holm, Sverre (2024). Physics-informed differentiable method for piano modeling. Frontiers in Signal Processing. ISSN 2673-8198. doi: 10.3389/frsip.2023.1276748.
  • Lucas Bravo, Pedro Pablo & Fasciani, Stefano (2023). A Human-Agents Music Performance System in an Extended Reality Environment. In Ortiz, Miguel & Marquez-Borbon, Adnan (Ed.), Proceedings of the International Conference on New Interfaces for Musical Expression. Universidad Autónoma Metropolitana. ISSN 2220-4792. Full text in Research Archive
  • Simionato, Riccardo & Fasciani, Stefano (2023). Fully Conditioned and Low-latency Black-box Modeling of Analog Compression. In Serafin, Stefania; Fontana, Federico & Willemsen, Silvin (Ed.), Proceedings of the 26th International Conference on Digital Audio Effects. Aalborg University Copenhagen. ISSN 2413-6700. p. 287–295. Full text in Research Archive
  • Simionato, Riccardo & Fasciani, Stefano (2023). A Comparative Computational Approach to Piano Modeling Analysis, Proceedings of the Sound and Music Computing Conference 2023. SMC Network . ISSN 978-91-527-7372-7.
  • von Arnim, Hugh Alexander; Fasciani, Stefano & Erdem, Cagri (2023). The Feedback Mop Cello: An Instrument for Interacting with Acoustic Feedback Loops. In Ortiz, Miguel & Marquez-Borbon, Adnan (Ed.), Proceedings of the International Conference on New Interfaces for Musical Expression. Universidad Autónoma Metropolitana. ISSN 2220-4792. doi: http:/hdl.handle.net/10852/104236. Full text in Research Archive
  • Afsari, Kiyan; El Barachi, May; Fasciani, Stefano & Belqasmi, Fatna (2022). A Deep Learning Approach for Real-time Detection of Epileptic Seizures using EEG, 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech). IEEE conference proceedings. ISSN 978-1-6654-8828-0. doi: 10.23919/SpliTech55088.2022.9854359.
  • Simionato, Riccardo & Fasciani, Stefano (2022). Deep Learning Conditioned Modeling of Optical Compression. Proceedings of the International Conference on Digital Audio Effects. ISSN 2413-6700. Full text in Research Archive
  • Goode, Jackson Montgomery & Fasciani, Stefano (2022). A Toolkit for the Analysis of the NIME Proceedings Archive. In McPherson, Andrew & Frid, Emma (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: 10.21428/92fbeb44.58efca21. Full text in Research Archive
  • 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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  • 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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Published May 6, 2019 3:32 PM - Last modified Jan. 6, 2024 1:54 PM
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Projects