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The MusAI research program comprises a large interdisciplinary team of early career and leading researchers and practitioners based around the world. Research team members comes from digital anthropology and sociology, musicology, science and technology studies, digital media and critical data studies, music composition and music research, computer science, computational creativity and music information retrieval. Our Advisory Board brings expertise from these fields, from musicians working critically with AI, and from industry.  

Core Research Team 

Georgina Born (University College London)

Image of Georgina Born

Principal Investigator

Georgina Born is Professor of Anthropology and Music at University College London. Previously she held Professorships at the Universities of Oxford (2010-21) and Cambridge (2006-10). She also had a professional life as a musician in experimental rock, jazz and free improvisation. Her work combines ethnographic and theoretical writings on music, sound, television and digital media. Books include Rationalizing Culture: IRCAM, Boulez, and the Institutionalization of the Musical Avant-Garde (1995), Western Music and Its Others (ed. with D. Hesmondhalgh, 2000), Uncertain Vision (2004), Music, Sound and Space (ed., 2013), Interdisciplinarity (ed. with A. Barry, 2013), Improvisation and Social Aesthetics (ed. with E. Lewis and W. Straw, 2017), and Music and Digital Media: A Planetary Anthropology (ed., 2022). She directed the ERC-funded research program Music, Digitization, Mediation (2010-15) and in 2021 was awarded an ERC grant for Music and Artificial Intelligence: Building Critical Interdisciplinary Studies. She has held visiting professorships at UC Berkeley, UC Irvine and Aarhus, Oslo, McGill and Princeton Universities.

Publications

2022. Music and Digital Media: A Planetary Anthropology. (Editor.) London: UCL Press (open access).

2021. (With Jeremy Morris, Fernando Diaz and A. Anderson). Artificial Intelligence, Music Recommendation, and the Curation of Culture: A White Paper. Toronto: Schwartz Reisman Institute for Technology and Society, University of Toronto.

2020. ‘Diversifying MIR: Knowledge and real-world challenges, and new interdisciplinary futures’, Transactions of the International Society for Music Information Retrieval, v. 4: 1-12.

2018. Music, Mediation Theories and Actor-Network Theory. (Editor.) Special issue of the Contemporary Music Review, v. 37, n. 5–6.

2018. ‘Principles of public service for the 21st century’, Chapter 13, pp. 130-140, in D. Freedman and V. Goblot (eds.), A Future for Public Service Television. London: Goldsmiths/MIT Press.

2018. ‘Taking the principles of public service media into the digital ecology’, Chapter 23, pp. 181-190, in D. Freedman and V. Goblot (eds.), A Future for Public Service Television. London: Goldsmiths/MIT Press.

2018. ‘On nonhuman sound: Sound as relation’, Chapter 10, pp. 185-210, in R. Chow and J. Steintrager (eds.), Sound Objects. Durham, NC: Duke University Press.

2017. (With Christopher Haworth) ‘From microsound to vaporwave: Internet-mediated musics, online methods, and genre’, Music and Letters, v. 98, n. 4: 601-47.

Oliver Bown (University of New South Wales, Sydney)

Image of Oliver Bown

Oliver Bown is associate professor and co-director of the Interactive Media Lab at the School of Art and Design at the University of New South Wales, in Sydney, Australia. He is a researcher and maker working with creative technologies, with a highly diverse academic background spanning social anthropology, evolutionary and adaptive systems, music informatics and interaction design, with a parallel career in electronic music and digital art spanning over 15 years. He is interested in how artists, designers and musicians can use advanced computing technologies to produce complex creative works. His current active research areas include media multiplicities, musical metacreation, the theories and methodologies of computational creativity, new interfaces for musical expression, and multi-agent models of social creativity.

Publications

Bown, O., 2021. Beyond the Creative Species: Making Machines that Make Art and Music. MIT Press.

Bown, O., 2021. Sociocultural and design perspectives on AI-based music production: why do we make music and what changes if ai makes it for us?. In Handbook of Artificial Intelligence for Music (pp. 1-20). Springer, Cham.

Bown, O. and Brown, A.R., 2018. Interaction design for metacreative systems. In New Directions in Third Wave Human-Computer Interaction: Volume 1-Technologies (pp. 67-87). Springer, Cham.

Eldridge, A. and Bown, O., 2018. Biologically inspired and agent-based algorithms for music.

Bown, O., 2018. Performer interaction and expectation with live algorithms: experiences with Zamyatin. Digital Creativity, 29(1), pp.37-50.

Aaron Einbond (City University, London)

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Aaron Einbond’s work explores the intersection of instrumental music, field recording, sound installation, and interactive technology. Chicago-based Ensemble Dal Niente released his portrait album Without Words on Carrier Records and he collaborated with Yarn/Wire and Matilde Meireles on the album Cities released on multi.modal. Alvise Sinivia premiered Cosmologies for piano and three-dimensional electronics produced by IRCAM at Centre Georges Pompidou in Paris, SWR Experimentalstudio produced Cartographies for piano with two performers and electronics for the Kubus at ZKM in Karlsruhe, and the Académie du Festival d’Aix and Opera Lab Berlin co-produced his site-specific ambient chamber opera Hidden in Plain Sight in the streets of Aix-en-Provence. Other recent collaborators include the Riot Ensemble, soundinitiative, Lucilin, loadbang, TAK, Séverine Ballon, and Samuel Stoll. He teaches at City, University of London and is Co-Artistic Director of Qubit New Music in New York. He has received a John Simon Guggenheim Memorial Foundation Fellowship, a Giga-Hertz Förderpreis, and Artistic Research Residencies at IRCAM and ZKM. He has taught at Columbia University, the University of Huddersfield, and Harvard University and studied at Harvard University, the University of Cambridge, the University of California Berkeley, and IRCAM with teachers including Mario Davidovsky, Julian Anderson, Edmund Campion, and Philippe Leroux.

Publications

2022. Einbond, Aaron. Prestidigitation for percussion and 3D electronics, Maxime Echardour, Mercredis de STMS, IRCAM, Paris, 2022. Video and binaural recording: https://youtu.be/j0kywabT0WQ

2021. Einbond, Aaron, Jean Bresson, Diemo Schwarz, and Thibaut Carpentier. “Instrumental Radiation Patterns as Models for Corpus-Based Spatial Sound Synthesis: Cosmologies for Piano and 3D Electronics.” Proceedings of the International Computer Music Conference (ICMC), Santiago, 2021. https://openaccess.city.ac.uk/26295/

2020. Einbond, Aaron. Cosmologies for piano und 3D electronics, STARTS Residency Commission, Alvise Sinivia, piano IRCAM Live, Grande Salle, Centre Georges Pompidou, Paris, 2020. Video and binaural recording: https://youtu.be/jKIWLwPrun4

2017. Einbond, Aaron. “Mapping the Klangdom Live: Cartographies for piano with two performers and electronics.” Computer Music Journal, 41:1, 2017. https://openaccess.city.ac.uk/17394/

2016. Einbond, Aaron, Diemo Schwarz, Riccardo Borghesi, and Norbert Schnell. “Introducing CatOracle: Corpus-based concatenative improvisation with the Audio Oracle algorithm.” Proceedings of ICMC, Utrecht, 2016. https://openaccess.city.ac.uk/15424/

Artemi-Maria Gioti (University College London)

Image of Artemi-Maria Gioti

Artemi-Maria Gioti is a composer and artistic researcher working in the field of artificial intelligence. Her research explores the transformative potential of new technologies for musical thinking and seeks to redefine notions of authorship, performership and the construct of the musical work. Interactivity is a central focus of her art and research, which views the musical work as the product of collaborative and distributed human-human and human-computer co-creativity.

She studied Composition, Electroacoustic Composition and Computer Music at the University of Macedonia (Greece), the University of Music and Performing Arts Vienna and the University of Music and Performing Arts Graz. She holds a doctoral degree in Music Composition from the University of Music and Performing Arts Graz. She is currently a Lecturer at the University of Music Carl Maria von Weber Dresden and a Research Fellow in Music and Artificial Intelligence at University College London (UCL), working on MusAI.

Website: artemigioti.com

Christopher Haworth (University of Birmingham)

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Christopher Haworth is Associate Professor in Music at the University of Birmingham. His research spans a number of topics in twentieth and twenty-first century musics including electronic and experimental musics; British popular music; music and politics; the theory and analysis of music technology; and music and the internet. He is currently completing a historical monograph examining the relationship between popular music and revolutionary theory in 1990s Britain, as groups like the CCRU and TechNET retooled left-aligned theories of political change for the emerging world wide web. Additionally, Christopher is working on an edited collection, The Digital Sociology of Music, which stems from his 2019-21 AHRC Early Career Leadership Fellowship of the same title. Christopher’s articles have appeared in Theory Culture Society, Computer Music Journal, Music and Letters, Leonardo Music Journal, and Organised Sound, as well as several edited collections. Christopher is also an electronic musician with interests in sound synthesis, spatialisation, and psychoacoustics.

Publications

2022. “Total Immersion: Did post-punk and industrial culture zines give us the information dark age?”, Theory, Culture, Society, 39 (7-8) (Accepted, publication December 2022).

2021. “Music and Cybernetics in Historical Perspective” (co-edited with Eric Drott).  Resonance: Journal of Sound and Culture. California:  University of California Press.

2020. “Digital Utopianism in Early Network Music: The Rise and Fall of The Res Rocket Surfer Band” In: Robert Adlington and Esteban Buch (eds), Finding Democracy in Music, London: Routledge (Musical Cultures of the Twentieth Century series).

2018. “Protentions and Retentions of Xenakis and Cage: Nonhuman Actors, Genre and Time in Microsound”, Contemporary Music Review, 35 (1-2), 606-625.

2017. “From Microsound to Vaporwave: Internet-mediated musics, online methods, and genre.” Music and Letters, 98(4), pp.601-647, joint-authored with Georgina Born (winner of Music and Letters’ Annual Westrup Prize for the best article published in the journal)

Darci Sprengel (Kings College London)

Image of Darci Sprengel

Darci Sprengel is a Lecturer in the Music Industry in the department of Culture, Media and the Creative Industries at King’s College London. Her current research analyses the imperial politics of music streaming technologies in the Southwest Asia and North Africa region using ethnography and feminist and critical race approaches to digital media. Her current work builds from fifteen years of ethnographic research among musicians and activists in Egypt’s independent music scenes. She has published in Popular Music, Culture, Theory & Critique, International Journal of Middle East Studies, International Journal of Cultural Studies, and Sound Studies. She was previously an Assistant Professor of Popular Music at the University of Groningen (Netherlands) and a Junior Research Fellow at the University of Oxford. She received her PhD in ethnomusicology with a concentration in gender studies from the University of California, Los Angeles. 

Publications

Articles:

Under review. “From Grassroots Initiatives to Imperial Lag: Theorizing the Platformisation of the Creative Industries from the Global South.”  

Under review. “Research Partnerships between Ethnographers and the Music Tech Industry: Possibilities and Limitations.”  

2020. “Reframing the ‘Arab Winter’: The Importance of Sleep and a Quiet Atmosphere after ‘Defeated’ Revolutions.” Culture, Theory & Critique 61 (2-3): 246-266. 

2020. “‘Loud’ and ‘Quiet’ Politics: Questioning the Role of ‘the Artist’ in Street Art Projects after the 2011 Egyptian Revolution.” International Journal of Cultural Studies 23 (2): 208-226. 

Book chapters:

In preparation “Data Colonization and Its Refusals: The Case of Egypt’s Independent Music Scenes.” In Digital Platforms in the Global South: Shaping a Critical Approach, edited by Philip Bouquillion, Christina Ithurbide, and Tristan Mattelart. London: Routledge. 

Under review. “The Classed, Gendered, and Imperial Politics of Digital Distribution in the Arabic Music Industry.” In The Oxford Handbook to the Global Music Industries, edited by K.E. Goldschmitt and Jayson Beaster-Jones. Oxford: Oxford University Press. 

Under review. “Curating Tarab on Music Streaming Services: The Cultural Politics of Localization and Algorithmic Bias on Spotify, Anghami, and Deezer.” In Ṭarab: Music, Ecstasy, Emotion, and Performance, edited by Michael Frishkopf, Dwight Reynolds, and Scott Marcus. Austin: University of Texas Press. 

Researchers

Fernando Diaz (McGill University; Mila; Google)

Image of Fernando Diaz

Fernando Diaz is a research scientist at Google Research Montréal. His research focuses on the design of information access systems, including search engines, music recommendation services and crisis response platforms. He is particularly interested in understanding and addressing the societal implications of artificial intelligence more generally. Previously, Fernando was the assistant managing director of Microsoft Research Montréal and a director of research at Spotify, where he helped establish its research organization on recommendation, search, and personalization. Fernando’s work has received awards at SIGIR, WSDM, ISCRAM, and ECIR. He is the recipient of the 2017 British Computer Society Karen Spärck Jones Award. Fernando has co-organized workshops and tutorials at SIGIR, WSDM, and WWW. He has also co-organized several NIST TREC initiatives, WSDM (2013), Strategic Workshop on Information Retrieval (2018), FAT* (2019), SIGIR (2021), and the CIFAR Workshop on Artificial Intelligence and the Curation of Culture (2019).    

Publications

2022. A. Ferraro, G. Ferreira, F. Diaz, G. Born. Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship. RecSys (Late Breaking Results)

2022. F. Diaz, A. Ferraro. Offline Retrieval Evaluation Without Evaluation Metrics. SIGIR

2020. F. Diaz, B. Mitra, M. D. Ekstrand, A. J. Biega, B. Carterette. Evaluating Stochastic Rankings with Expected Exposure. CIKM

2018. J. Garcia-Gathright, B. St. Thomas, C. Hosey, Z. Nazari, F. Diaz. Understanding and Evaluating User Satisfaction with Music Discovery. SIGIR

2017. R. Mehrotra, A. Anderson, F. Diaz, A. Sharma, H. Wallach, E. Yilmaz. Auditing Search Engines for Differential Performance Across Demographics. WWW

Eric Drott (University of Texas, Austin)

Eric Drott

Eric Drott is associate professor of music theory at the University of Texas at Austin. His research spans a number of subjects: contemporary music cultures, streaming music platforms, music and protest, genre theory, digital music, and the political economy of music. His first book, Music and the Elusive Revolution (University of California Press, 2011), examines music and politics in France after May ’68, in particular how different music communities (jazz, rock, contemporary music) responded to the upheavals of the period. His second book, titled Streaming Music, Streaming Capital, is forthcoming from Duke University Press. He is also co-editing the Oxford Handbook of Protest Music with Noriko Manabe (Temple University).

Publications

2022. ‘Is your baby getting enough music?’ Musical interventions into gestational labor. With Marie Thompson. Women and Music 26: 122-144

2021. Music and the Cybernetic Mundane. Resonance 2 no. 4: 578-599.

2020. Copyright, Compensation, and Commons in the Music AI Industry. Creative Industries Journal: 190-207.

2020. Fake Streams, Listening Bots, and Click Farms: Counterfeiting Attention in the Streaming Music Economy. American Music 38 no. 2: 153-175.

2019. Music and Socialism: Three Moments. Twentieth Century Music 16 no. 1: 7-31.

2019. Music in the Work of Social Reproduction. Cultural Politics 15 no. 2: 162-183.

2018. Why the Next Song Matters: Streaming, Recommendation, Scarcity. Twentieth Century Music 15 no. 3: 325-357.

2018. Music as a Technology of Surveillance. Journal of the Society for American Music 12 no. 3: 233-267.

Andrés Ferraro (McGill University; Pandora)

Andres Ferraro

Andrés Ferraro (BSc/MSc in Software Engineering) is a Postdoctoral Fellow at McGill University and Mila (Quebec AI Institute), Canada. He completed his PhD at the Department of Information and Communication Technologies and Engineering of the Universitat Pompeu Fabra, Spain. His thesis uncovers multiple dimensions in which music recommender systems affect the artists and proposes alternatives to mitigate such problems. He is currently part of the MusAI project, rethinking music recommender systems by considering new and alternative conceptions from the social sciences and humanities, informed by non-profit systems and critical debates over bias and discrimination. He is co-organizer of LatAm Bish Bash, a series of meetings and networking events that connect engineers, researchers, and students from Latin America working on music and audio signal processing.

Publications

2022. A. Ferraro, G. Ferreira, G. Born and F. Diaz “Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship”. In Proc. of the 16th ACM Conf. on Recommender Systems.

2022. P. Knees, A. Ferraro and M. Hübler “Bias and Feedback Loops in Music Recommendation: Studies on Record Label Impact”. In MORS22 workshop at the 16th ACM Conf. on Recommender Systems.

2022. F. Diaz and A. Ferraro “Offline Retrieval Evaluation Without Evaluation Metrics”. In ACM SIGIR Conference on Research and Development in Information Retrieval SIGIR 22

2021. A. Ferraro, X. Serra and C. Bauer. “What is fair? Exploring the artists’ perspective on fairness of music streaming platforms”. In Proc. of 18th IFIP Int. Conf. on Human-Computer Interaction.

2021. A. Ferraro, X. Serra and C. Bauer. “Break the Loop: Balancing Artists’ Gender with Music Recommenders”. In Proc. of 6th ACM SIGIR Conf. on Human Information Interaction and Retrieval.

2020. A. Ferraro, D. Jannach, and X. Serra. “Exploring Longitudinal Effects of Session-based Recommendations”. In Proc. of the 14th ACM Conf. on Recommender Systems.

Gustavo Ferreira (McGill University)

Gustavo Ferreira

Gustavo Ferreira holds a Ph.D. in Communication from the Universidade do Estado do Rio de Janeiro (UERJ), and a MA in Communication from the Universidade Federal do Paraná (UFPR), both in Brazil. He researches cultural mediations of communication technologies, currently focusing on interdisciplinary translations between Media studies and Computer Science approaches to Music Playlists and Recommender Systems. In particular, he questions the relationship between different audio media (Radio, Social Media and Streaming Platforms). His studies employ theories and methodologies from cultural studies and the political economy of culture and technology industries to explore global media dynamics, decoloniality and Latin-American communication, and politics of sound culture.

Publications

2022. Ferraro, A., Ferreira, G., Diaz, F., & Born, G. Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship.  In. New York, NY, USA: ACM. http://dx.doi.org/10.1145/3523227.3551476

2020. Ferreira, G. . O formato playlist :a prescrição musical entre filosofias de programação radiofônica e engenharias da experiência musical automática. [Tese, Universidade do Estado do Rio de Janeiro (UERJ)]. 

2017. Kischinhevsky, M., Benzecry, L., Mustafá, I., De Marchi, L., Chagas, L., Ferreira, G., Victor, R., & Viana, L. The consolidation of radio and sound media studies in the XXI century–Conceptual keys and research objects. Intercom-Revista Brasileira de Ciências da Comunicação, 40(3), 91-106. https://doi.org/https://doi.org/10.1590/1809-5844201736

2021. Kischinhevsky, M., Ferreira, G., Góes, C., Seidel, A., & Monteiro, L. Between algorithm and curation – Radio programming, music genres and repetition. Comunicação Mídia e Consumo, 18(51), 165. https://doi.org/10.18568/cmc.v18i51.2216

2021. de Marchi, L., Kischinhevsky, M., Ferreira, G., & Saldanha, R. M. O gosto algorítmico: A lógica dos sistemas de recomendação automática de música em serviços de streaming. Fronteiras – estudos midiáticos, 23(3), 16-26. https://doi.org/https://doi.org/10.4013/fem.2021.233.02

2021. Ferreira, G., & Saldanha, R. M. Ruídos do carnaval: política, cultura e paisagens sonoras dos blocos de rua de São Paulo e Rio de Janeiro. Tropos: Comunicação, Sociedade e Cultura, 10(2). https://periodicos.ufac.br/index.php/tropos/article/view/4909

Rebecca Fiebrink (University of the Arts, London)

Rebecca Fiebrink

Rebecca Fiebrink makes new accessible and creative technologies. As a Professor at the Creative Computing Institute at University of the Arts London, her teaching and research focus largely on how machine learning and artificial intelligence can change human creative practices. She is the developer of the Wekinator creative machine learning software, which is used around the world by musicians, artists, game designers, and educators. She is the creator of the world’s first online class about machine learning for music and art. Much of her work is driven by a belief in the importance of inclusion, participation, and accessibility: current and recent projects include creating new accessible technologies with people with disabilities, and working with the Decolonising Arts Institute and Tate to build machine learning tools for addressing bias and uncovering hidden connections in art collections across the UK. Prof. Fiebrink previously taught at Goldsmiths University of London and Princeton University, and she has worked with companies including Microsoft, Smule, and Imagine Research. She holds a PhD in Computer Science from Princeton University.

Publications

2021. Hilton, C., N. Plant, C. González Díaz, P. Perry, R. Gibson, B. Martelli, M. Zbyszynski, R. Fiebrink, and M. Gillies. 2021. “InteractML: Making machine learning accessible for creative practitioners working with movement interaction in immersive media.” In Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology (VRST).

2020. Bernardo, F., M. Zbyszyński, M. Grierson and R. Fiebrink. 2020. “Designing and evaluating the usability of an API for rapid prototyping music technology with interactive machine learning.” Frontiers in Artificial Intelligence 3(13): 1–18.

2019. Fiebrink, R. 2019. “Machine Learning Education for Artists, Musicians, and Other Creative Practitioners.” ACM Transactions on Machine Learning Education, Sept 2019. Article No.: 31.

2019. Parke-Wolfe, S. T., H. Scurto, and R. Fiebrink. 2019. “Sound Control: Supporting Custom Musical Interface Design for Children with Disabilities.” In Proceedings of the International Conference on New Instruments for Musical Expression (NIME).

2015. Katan, S., M. Grierson, and R. Fiebrink. 2015. “Using interactive machine learning to support interface development through workshops with disabled people.” In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI’15).

2011. Fiebrink, R., P. R. Cook, and D. Trueman. 2011. “Human model evaluation in interactive supervised learning.” Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI’11).

2009. Fiebrink, R., D. Trueman, and P. R. Cook. 2009. “A meta-instrument for interactive, on-the-fly learning.” Proceedings of the International Conference on New Instruments for Musical Expression (NIME).

Owen Green (Max Planck Institute for Empirical Aesthetics; UCL)

Owen Green

Owen Green‘s research centres on live electronic music, with focuses on playing with and designing semi-autonomous performance systems, and the philosophy of technology as it relates to music. Most recently, Owen has worked as a postdoctoral fellow on the Fluid Corpus Manipulation project at the University of Huddersfield, where he has been in involved in research that puts machine listening and machine learning tools into the hands of musicians working in Max, SuperCollider and Pure Data. Emerging from this, a current topic of particular interest is how music technology as a discipline can better discover and interact with its publics to account for and support a wider ranges of ideas and practices. Owen joins MusAI in Spring 2023, working on the project ‘Sonic-Social Genre?: Towards Multimodal Computational Music Genre Modelling’ with Georgina Born, Bob Sturm and Melanie Wald-Fuhrmann.  

Publications

2022. Tremblay, P. A., Roma, G., & Green, O. Enabling Programmatic Data Mining as Musicking: The Fluid Corpus Manipulation Toolkit. Computer Music Journal, 45(2), 9–23. https://doi.org/10.1162/comj_a_00600

2018. Bowers, J., & Green, O. All the Noises: Hijacking Listening Machines for Performative Research. In T. M. Luke Dahl, Douglas Bowman (Ed.), Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 114–119). Virginia Tech. http://www.nime.org/proceedings/2018/nime2018_paper0026.pdf

2018. Green, O., Tremblay, P. A., & Roma, G. Interdisciplinary Research as Musical Experimentation: A case study in musicianly approaches to sound corpora. Electroacoustic Studies Network Conference, Florence, Italy.

2014. Green, O. NIME, Musicality and Practice-led Methods. In B. Caramiaux, K. Tahiroglu, R. Fiebrink, & A. Tanaka (Eds.), Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 1–6). Goldsmith’s University of London. http://www.nime.org/proceedings/2014/nime2014_434.pdf

2011. Green, O. Agility and Playfulness: Technology and skill in the performance ecosystem. Organised Sound, 16(2), 134–144. https://doi.org/10.1017/S1355771811000082

Jonathan Sterne (McGill University)

Jonathan Sterne

Jonathan Sterne teaches in the Department of Art History and Communication Studies at McGill University.  He is the author of Diminished Faculties: A Political Phenomenology of Impairment (Duke 2021); MP3: The Meaning of a Format (Duke 2012), The Audible Past: Cultural Origins of Sound Reproduction (Duke 2003), and numerous articles on media, technologies and the politics of culture.  He is also editor of The Sound Studies Reader (Routledge 2012) and co-editor of The Participatory Condition in the Digital Age (Minnesota 2016).  He is working on a series of essays on artificial intelligence and culture, and with Mara Mills he is writing Tuning Time: Histories of Sound and Speed. Visit his website at http://sterneworks.org. As a researcher, Sterne employs historiographic, philosophical and interpretive methods, interviews, and participant observation. In addition to his books and articles, Sterne has published online since 1994, experimenting with multimodal and open access approaches.

Sterne has held fellowships from the Mellon and Woodrow Wilson Foundations, the Smithsonian Institution, the Center for Advanced Study in the Behavioral Sciences at Stanford University, the University of Southern California, and the Max Planck Institute for the History of Science in Berlin. He has been a visiting scholar at Harvard and New York Universities, and a visiting researcher in the Social Media Collective at Microsoft Research New England and Microsoft Research New York. He has delivered over a hundred invited lectures and keynotes around the world and has been widely translated.

Publications

2021. Diminished Faculties: A Political Phenomenology of Impairment (Duke University Press)

2012. MP3: The Meaning of a Format (Duke University Press)

2003. The Audible Past: Cultural Origins of Sound Reproduction (Duke University Press)

As editor or co-editor:

2016. The Participatory Condition in the Digital Age (University of Minnesota Press)

2013. The Politics of Academic Labor in Communication Studies (Annenberg Press)

2012. The Sound Studies Reader (Routledge) 

2021. Co-authored with Elena Razlogova, “Tuning Sound for Infrastructures: Artificial Intelligence, Automation, and the Cultural Politics of Audio Mastering,” Cultural Studies 35:2.

2020. Co-authored with Mara Mills, “Second Rate: Tempo Regulation, Helium Speech, and ‘Information Overload,’” Triple Canopy #26: https://www.canopycanopycanopy.com/issues/26/contents/second-rate

2020. Co-authored with Mara Mills, “Aural Speed Reading: Some Historical Bookmarks,” PMLA (Publications of the Modern Language Association)135:2: 401-411.

2020. “The Software Passes the Test When the User Fails It: Constructing Digital Models of Analog Signal Processors,” Testing Hearing, eds. Viktoria Traczyk, Mara Mills and Alexandra Hui, 159-185. New York: Oxford University Press.

2019. Co-authored with Elena Razlogova, “Machine Learning in Context, or Learning from LANDR: Artificial Intelligence and the Platformization of Music Mastering,” Social Media + Society 5:2 (April-June): 1-18.

Bob L. T. Sturm (KTH Royal Institute of Technology, Stockholm)

Bob Sturm

Bob L. T. Sturm is Associate Professor of Computer Science at the KTH Royal Institute of Technology, Stockholm, Sweden. He has degrees in physics, music, multimedia, and engineering, and specializes in signal processing and machine learning applied to music data. He currently leads the MUSAiC project funded by the European Research Council (https://musaiclab.wordpress.com), and is probably most known for his work on horses, the GTZAN dataset, and playing Ai generated folk music on his accordion (https://tunesfromtheaifrontiers.wordpress.com).

Publications

2021. R. Huang and B. L. T. Sturm, “Reframing “aura”: Authenticity in the application of ai to irish traditional music,” in Proc. AI Music Creativity.

2021. B. L. T. Sturm and O. Ben-Tal, Handbook of Artificial Intelligence for Music, ch. Folk the Algorithms: (Mis)Applying Artificial Intelligence to Folk Music. Springer.

2019. B. L. Sturm, M. Iglesias, O. Ben-Tal, M. Miron, and E. G ́omez, “Artificial intelligence and music: Open questions of copyright law and engineering praxis,” MDPI Arts, vol. 8, no. 3.

2018. B. L. Sturm, O. Ben-Tal, U. Monaghan, N. Collins, D. Herremans, E. Chew, G. Hadjeres, E. Deruty, and F. Pachet, “Machine learning research that matters for music creation: A case study,” J. New Music Research, vol. 48, no. 1, pp. 36–55.

2014. B. L. Sturm, “A survey of evaluation in music genre recognition,” in Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation (A. Nu ̈rnberger, S. Stober, B. Larsen, and M. Detyniecki, eds.), vol. LNCS 8382, pp. 29–66.

2014. B. L. Sturm, “The state of the art ten years after a state of the art: Future research in music information retrieval,” J. New Music Research, vol. 43, no. 2, pp. 147–172.

2014. B. L. Sturm, “A simple method to determine if a music information retrieval system is a “horse”,” IEEE Trans. Multimedia, vol. 16, no. 6, pp. 1636–1644

2013. B. L. Sturm, “Classification accuracy is not enough: On the evaluation of music genre recognition systems,” J. Intell. Info. Systems, vol. 41, no. 3, pp. 371–406.

Advisory Board

Caroline Bassett (University of Cambridge)
Nancy Baym (Microsoft Research)
Tobias Blanke (University of Amsterdam)
Kate Crawford (USC Annenberg; Microsoft Research)
Bernard Geoghagen (Kings College London)
Holly Herndon
David Hesmondhalgh (University of Leeds)
Adrian Mackenzie (Australian National University)
Robert Prey (University of Groningen)
Rida Qadri (Google Research)
Nick Seaver (Tufts University)
Lucy Suchman (Lancaster University)
Jennifer Walshe (University of Oxford)
Brian Whitman