TU Wien Informatics

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Peter Knees

Associate Prof. Dipl.-Ing. Dr.techn.

Research Focus

  • Information Systems Engineering: 70%
  • Visual Computing and Human-Centered Technology: 30%

Research Areas

  • Information Retrieval, User interfaces, Music Information Retrieval, Recommender Systems, Artificial Intelligence, Machine Learning
Peter Knees

Roles

  • Associate Professor
    Data Science, E194-04
  • Curriculum Coordinator
    Bachelor Informatics / Specialization Artificial Intelligence + Machine Learning
  • Faculty Council
    Substitute Member

Contact

2023W

 

2023

2022

  • On the Impact and Interplay of Input Representations and Network Architectures for Automatic Music Tagging / Damböck, M., Vogl, R., & Knees, P. (2022). On the Impact and Interplay of Input Representations and Network Architectures for Automatic Music Tagging. In P. Rao, H. Murphy, A. Srinivasamurthy, R. Bittner, R. Caro Repetto, M. Goto, X. Serra, & M. Miron (Eds.), Proceedings of the 23rd International Society for Music Information Retrieval Conference. ISMIR 2022 (pp. 941–948). International Society for Music Information Retrieval. https://doi.org/10.5281/zenodo.7343091
    Download: PDF (655 KB)
    Project: HumRec (2021–2024)
  • A Reproducibility Study on User-centric MIR Research and Why it is Important / Knees, P., Ferwerda, B., Rauber, A., Strumbelj, S., Resch, A., Tomandl, L., Bauer, V., Tang, F. Y., Bobinac, J., Ceranic, A., & Dizdar, R. (2022). A Reproducibility Study on User-centric MIR Research and Why it is Important. In P. Rao, H. Murthy, A. Srinivasamurthy, R. Bittner, R. Caro Repetto, M. Goto, X. Serra, & M. Miron (Eds.), Proceedings of the 23rd International Society for Music Information Retrieval (ISMIR) Conference (pp. 764–771). International Society for Music Information Retrieval. https://doi.org/10.5281/zenodo.7316775
    Download: Camera-ready version (150 KB)
    Project: HumRec (2021–2024)
  • Bias and Feedback Loops in Music Recommendation: Studies on Record Label Impact / Knees, P., Ferraro, A., & Hübler, M. (2022). Bias and Feedback Loops in Music Recommendation: Studies on Record Label Impact. In H. Abdollahpouri, S. Sahebi, M. Elahi, M. Mansoury, B. Loni, Z. Nazari, & M. Dimakopoulou (Eds.), MORS 2022. Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems, co-located with 16th ACM Conference on Recommender Systems (RecSys 2022. CEUR-WS.org. https://doi.org/10.34726/3723
    Download: Camera-ready version (1.13 MB)
    Project: HumRec (2021–2024)
  • Music Information Retrieval and Recommendation: Recent and Future Developments / Knees, P. (2022, August 22). Music Information Retrieval and Recommendation: Recent and Future Developments [Presentation]. Georgia Tech Center for Music Technology Seminar Series, Atlanta, GA, United States of America (the).
  • ReStyle-MusicVAE: Enhancing User Control of Deep Generative Music Models with Expert Labeled Anchors / Prvulovic, D., Vogl, R., & Knees, P. (2022). ReStyle-MusicVAE: Enhancing User Control of Deep Generative Music Models with Expert Labeled Anchors. In A. Bellogin, L. Boratto, O. C. Santos, L. Ardissono, & B. Knijnenburg (Eds.), Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 63–66). Association for Computing Machinery. https://doi.org/10.1145/3511047.3536412
    Project: HumRec (2021–2024)
  • Scaling Up Broken Systems? Considerations from the Area of Music Streaming / Knees, P. (2022). Scaling Up Broken Systems? Considerations from the Area of Music Streaming. In H. Werthner, E. Prem, E. A. Lee, & C. Ghezzi (Eds.), Perspectives on Digital Humanism (pp. 165–171). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-86144-5_23

2021

2020

2019

  • Intelligent User Interfaces for Music Discovery: The Past 20 Years and What's to Come / Knees, P., Schedl, M., & Goto, M. (2019). Intelligent User Interfaces for Music Discovery: The Past 20 Years and What’s to Come. In A. Flexer, G. Peeters, J. Urbano, & A. Volk (Eds.), Proceedings of the 20th International Society for Music Information Retrieval Conference (pp. 44–53). Zenodo. https://doi.org/10.5281/zenodo.3527737
  • Multi-Task Learning of Tempo and Beat: Learning One to Improve the Other / Böck, S., Davies, M., & Knees, P. (2019). Multi-Task Learning of Tempo and Beat: Learning One to Improve the Other. In A. Flexer, G. Peeters, J. Urbano, & A. Volk (Eds.), Proceedings of the 20th International Society for Music Information Retrieval Conference (pp. 486–493). Zenodo. https://doi.org/10.5281/zenodo.3527849
  • Predicting user demographics from music listening information / Krismayer, T., Schedl, M., Knees, P., & Rabiser, R. (2019). Predicting user demographics from music listening information. Multimedia Tools and Applications, 78(3), 2897–2920. https://doi.org/10.1007/s11042-018-5980-y
    Project: SmarterJam (2017–2019)
  • Towards an alliance for distributed music data? / Sağlam, H., Hofmann, A., Ahmedaja, A., Miksa, T., & Knees, P. (2019). Towards an alliance for distributed music data? 45th International Council for Traditional Music World Conference, Bangkok, Thailand, Non-EU. http://hdl.handle.net/20.500.12708/87007
  • On Stakeholders and Data Biases in Music Recommendation / Knees, P. (2019). On Stakeholders and Data Biases in Music Recommendation. Media Technology and Interaction Design Seminar, KTH Stockholm, Sweden, EU. http://hdl.handle.net/20.500.12708/87011
  • From a Critical Take on Music Recommendation to Digital Humanism / Knees, P. (2019). From a Critical Take on Music Recommendation to Digital Humanism. Critical Perspectives on Data Science and Machine Learning, KTH Stockholm, Sweden, EU. http://hdl.handle.net/20.500.12708/87012
  • New Intelligent Tools in Music Creation? A Case for User-Centric Research / Knees, P. (2019). New Intelligent Tools in Music Creation? A Case for User-Centric Research. User Experience Design, Jönköping University, Sweden, EU. http://hdl.handle.net/20.500.12708/87010
  • Music Information Retrieval: Inside and Outside the Music / Bauer, C., & Knees, P. (2019). Music Information Retrieval: Inside and Outside the Music. Ars Electronica 2019 - AIxMusic Matinée, Linz, Austria. http://hdl.handle.net/20.500.12708/87009
  • Recommenders and Intelligent Tools in Music Creation: Why, Why Not, and How? / Bauer, C., Knees, P., Vogl, R., & Raber, H. (2019). Recommenders and Intelligent Tools in Music Creation: Why, Why Not, and How? Ars Electronica 2019 - AIxMusic Workshops, Linz, Austria. http://hdl.handle.net/20.500.12708/87008
  • Ethnomusicology meets Music Information Retrieval: Towards Automated Segmentation and Analysis / Knees, P. (2019). Ethnomusicology meets Music Information Retrieval: Towards Automated Segmentation and Analysis. 2nd Workshop on Distributed Ethnomusicology data and MIR in the framework of ASEA-UNINET, Mahidol University, Bangkok, Thailand, Non-EU. http://hdl.handle.net/20.500.12708/87006
  • Die perfekte Musikempfehlung - Perfekt für wen? / Knees, P. (2019). Die perfekte Musikempfehlung - Perfekt für wen? Future Music Camp 2019, Mannheim, Germany, EU. http://hdl.handle.net/20.500.12708/87005
  • Artificial Intelligence and the Future of Business / Knees, P., Wasner, C., & Krenn, B. (2019). Artificial Intelligence and the Future of Business. Vienna International Business Club, Expat Center of the Vienna Business Agency, Austria. http://hdl.handle.net/20.500.12708/87004
  • Introduction to Music Information Retrieval / Knees, P. (2019). Introduction to Music Information Retrieval. 1st Workshop on Distributed Ethnomusicology Data and Music Information Retrieval, Mahidol University, Bangkok, Thailand, Non-EU. http://hdl.handle.net/20.500.12708/87003
  • Towards Recommender Systems for Music Creators / Knees, P. (2019). Towards Recommender Systems for Music Creators. HCI Lunchtime Scientific Series, TU Wien, Austria. http://hdl.handle.net/20.500.12708/87002
  • Introduction to Music Information Retrieval / Knees, P. (2019). Introduction to Music Information Retrieval. Informatik BEGINNER’s Day 2019, TU Wien, Austria. http://hdl.handle.net/20.500.12708/87001
  • RecSys Challenge '19: Proceedings of the Workshop on ACM Recommender Systems Challenge / Knees, P., Deldjoo, Y., Bakhshandegan Moghaddam, F., Adamczak, J., Leyson, G.-P., & Monreal, P. (Eds.). (2019). RecSys Challenge ’19: Proceedings of the Workshop on ACM Recommender Systems Challenge. ACM. https://doi.org/10.1145/3359555
  • A Proposal for a Neutral Music Recommender System / Knees, P. (2019). A Proposal for a Neutral Music Recommender System. In M. Miron (Ed.), Proceedings of the 1st Workshop on Designing Human-Centric Music Information Research Systems (pp. 4–7). http://hdl.handle.net/20.500.12708/58098
  • Towards Uncovering Dataset Biases: Investigating Record Label Diversity in Music Playlists / Knees, P., & Hübler, M. (2019). Towards Uncovering Dataset Biases: Investigating Record Label Diversity in Music Playlists. In M. Miron (Ed.), Proceedings of the 1st Workshop on Designing Human-Centric Music Information Research Systems (pp. 19–22). http://hdl.handle.net/20.500.12708/58097
  • RecSys challenge 2019 / Knees, P., Deldjoo, Y., Moghaddam, F. B., Adamczak, J., Leyson, G.-P., & Monreal, P. (2019). RecSys challenge 2019. In Proceedings of the 13th ACM Conference on Recommender Systems. 13th ACM Conference on Recommender Systems, Copenhagen, Denmark, EU. ACM. https://doi.org/10.1145/3298689.3346974
  • Multi-Task Music Representation Learning from Multi-Label Embeddings / Schindler, A., & Knees, P. (2019). Multi-Task Music Representation Learning from Multi-Label Embeddings. In 2019 International Conference on Content-Based Multimedia Indexing (CBMI). 2019 International Conference on Content-Based Multimedia Indexing (CBMI), Dublin, Ireland, EU. IEEE. https://doi.org/10.1109/cbmi.2019.8877462
  • Intelligent music interfaces for listening and creation / Knees, P., Schedl, M., & Fiebrink, R. (2019). Intelligent music interfaces for listening and creation. In Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. 24th International Conference on Intelligent User Interfaces, Marina del Rey, CA, USA, Non-EU. ACM. https://doi.org/10.1145/3308557.3313110
  • Preface to the 2nd Workshop on Intelligent Music Interfaces for Listening and Creation (MILC) / Knees, P., Schedl, M., & Fiebrink, R. (2019). Preface to the 2nd Workshop on Intelligent Music Interfaces for Listening and Creation (MILC). In C. Trattner, D. Parra, & N. Riche (Eds.), Joint Proceedings of the ACM IUI 2019 Workshops (p. 2). CEUR-WS.org. http://hdl.handle.net/20.500.12708/58093
  • An automatic drum machine with touch UI based on a generative neural network / Vogl, R., Eghbal-Zadeh, H., & Knees, P. (2019). An automatic drum machine with touch UI based on a generative neural network. In Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion. 24th International Conference on Intelligent User Interfaces, Marina del Rey, CA, USA, Non-EU. ACM. https://doi.org/10.1145/3308557.3308673
  • 9. User awareness in music recommender systems / Knees, P., Schedl, M., Ferwerda, B., & Laplante, A. (2019). 9. User awareness in music recommender systems. In M. Augstein, E. Herder, & W. Wörndl (Eds.), Personalized Human-Computer Interaction (pp. 223–252). DeGruyter. https://doi.org/10.1515/9783110552485-009

2018

2017

2004