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Research Team听

听

Georgina Born听(University College London)

Principal Investigator

听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听Rationalizing Culture: IRCAM, Boulez, and the Institutionalization of the Musical Avant-Garde听(1995),听Western Music and Its Others听(ed. with D. Hesmondhalgh, 2000),听Uncertain Vision听(2004),听Music, Sound and Space听(ed., 2013),听Interdisciplinarity听(ed. with A. Barry, 2013),听Improvisation and Social Aesthetics听(ed. with E. Lewis and W. Straw, 2017), and听Music and Digital Media: A Planetary Anthropology听(ed., 2022). She directed the ERC-funded research program听Music, Digitization, Mediation听(2010-15) and in 2021 was awarded an ERC grant for听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.听听(Editor.) London: UCL Press (open access).

2021. (With Jeremy Morris, Fernando Diaz and A. Anderson).听.听Toronto: Schwartz Reisman Institute for Technology and Society, University of Toronto.

2020.听鈥楧iversifying MIR: Knowledge and real-world challenges, and new interdisciplinary futures鈥�, Transactions of the International Society for Music Information Retrieval, v. 4: 1-12.

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

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

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

2018.听鈥極n nonhuman sound: Sound as relation鈥�, Chapter 10, pp. 185-210, in R. Chow and J. Steintrager (eds.), Sound Objects. Durham, NC: Duke University Press.

2017. (With Christopher Haworth)听鈥楩rom microsound to vaporwave: Internet-mediated musics, online methods, and genre鈥�, Music and Letters, v. 98, n. 4: 601-47.

Oliver Bown听(University of New South Wales,听Sydney)

Oliver Bown听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.听Beyond the Creative Species: Making Machines that Make Art and Music.听MIT Press.

Bown, O., 2021.听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.听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.听Biologically inspired and agent-based algorithms for music.

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

Fernando Diaz听(Carnegie Mellon University, Google)

Fernando Diaz听is a research scientist at Google Research Montr茅al. 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 Montr茅al and a director of research at Spotify, where he helped establish its research organization on recommendation, search, and personalization. Fernando鈥檚 work has received awards at SIGIR, WSDM, ISCRAM, and ECIR. He is the recipient of the 2017 British Computer Society Karen Sp盲rck 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).听听听听

Publications

2022. A. Ferraro, G. Ferreira, F. Diaz, G. Born.听.听RecSys (Late Breaking Results)

2022. F. Diaz, A. Ferraro.听.听SIGIR

2020. F. Diaz, B. Mitra, M. D. Ekstrand, A. J. Biega, B. Carterette.听.听CIKM

2018. J. Garcia-Gathright, B. St. Thomas, C. Hosey, Z. Nazari, F. Diaz.听.听SIGIR

2017. R. Mehrotra, A. Anderson, F. Diaz, A. Sharma, H. Wallach, E. Yilmaz.听.听WWW

Eric Drott听(University of Texas, Austin)

Eric Drott听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 鈥�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.听鈥業s your baby getting enough music?鈥� Musical interventions into gestational labor. With Marie Thompson. Women and Music 26: 122-144

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

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

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

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

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

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

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

Aaron Einbond听(City University, London)

Aaron Einbond鈥檚听work explores the intersection of instrumental music, field recording, sound installation, and interactive technology. Chicago-based Ensemble Dal Niente released his portrait album听Without Words听on Carrier Records and he collaborated with Yarn/Wire and Matilde Meireles on the album听Cities听released on multi.modal. Alvise Sinivia premiered听Cosmologies听for piano and three-dimensional electronics produced by IRCAM at Centre Georges Pompidou in Paris, SWR Experimentalstudio produced听Cartographies听for piano with two performers and electronics for the Kubus at ZKM in Karlsruhe, and the Acad茅mie du Festival d鈥橝ix and Opera Lab Berlin co-produced his site-specific ambient chamber opera听Hidden in Plain Sight听in the streets of Aix-en-Provence. Other recent collaborators include the Riot Ensemble, soundinitiative, Lucilin, loadbang, TAK, S茅verine 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 F枚rderpreis, 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.听Prestidigitation for percussion and 3D electronics, Maxime Echardour, Mercredis de STMS, IRCAM, Paris, 2022. Video and binaural recording:听

2021. Einbond, Aaron, Jean Bresson, Diemo Schwarz, and Thibaut Carpentier.听鈥淚nstrumental Radiation Patterns as Models for Corpus-Based Spatial Sound Synthesis: Cosmologies for Piano and 3D Electronics.鈥澨齈roceedings of the International Computer Music Conference (ICMC), Santiago, 2021.听

2020.听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:

2017. Einbond, Aaron.听鈥淢apping the Klangdom Live: Cartographies for piano with two performers and electronics.鈥澨鼵omputer Music Journal,听41:1, 2017.听

2016. Einbond, Aaron, Diemo Schwarz, Riccardo Borghesi, and Norbert Schnell.听鈥淚ntroducing CatOracle: Corpus-based concatenative improvisation with the Audio Oracle algorithm.鈥澨齈roceedings of ICMC, Utrecht, 2016.听

Andr茅s Ferraro听(McGill University; Pandora)

Andr茅s 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 鈥淢easuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship鈥�. In Proc. of the 16th ACM Conf. on Recommender Systems.

2022. P. Knees, A. Ferraro and M. H眉bler 鈥淏ias and Feedback Loops in Music Recommendation: Studies on Record Label Impact鈥�. In MORS22 workshop at the 16th ACM Conf. on Recommender Systems.

2022. F. Diaz and A. Ferraro 鈥淥ffline Retrieval Evaluation Without Evaluation Metrics鈥�. In ACM SIGIR Conference on Research and Development in Information Retrieval SIGIR 22

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

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

2020. A. Ferraro, D. Jannach, and X. Serra. 鈥淓xploring Longitudinal Effects of Session-based Recommendations鈥�. In Proc. of the 14th ACM Conf. on Recommender Systems.

Gustavo Ferreira听(McGill University)

Gustavo Ferreira听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 Paran谩 (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.听Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship.听 In. New York, NY, USA: ACM.听

2020. Ferreira, G.听.听O formato playlist :a prescri莽茫o musical entre filosofias de programa莽茫o radiof么nica e engenharias da experi锚ncia musical autom谩tica.听[Tese, Universidade do Estado do Rio de Janeiro (UERJ)].听

2017. Kischinhevsky, M., Benzecry, L., Mustaf谩, I., De Marchi, L., Chagas, L., Ferreira, G., Victor, R., & Viana, L.听The consolidation of radio and sound media studies in the XXI century鈥揅onceptual keys and research objects. Intercom-Revista Brasileira de Ci锚ncias da Comunica莽茫o, 40(3), 91-106.听

2021. Kischinhevsky, M., Ferreira, G., G贸es, C., Seidel, A., & Monteiro, L.听Between algorithm and curation 鈥� Radio programming, music genres and repetition. Comunica莽茫o M铆dia e Consumo, 18(51), 165.听

2021. de Marchi, L., Kischinhevsky, M., Ferreira, G., & Saldanha, R. M.听O gosto algor铆tmico: A l贸gica dos sistemas de recomenda莽茫o autom谩tica de m煤sica em servi莽os de streaming.听Fronteiras 鈥� estudos midi谩ticos, 23(3), 16-26.听

2021. Ferreira, G., & Saldanha, R. M.听Ru铆dos do carnaval: pol铆tica, cultura e paisagens sonoras dos blocos de rua de S茫o Paulo e Rio de Janeiro.听Tropos: Comunica莽茫o, Sociedade e Cultura, 10(2).听

Rebecca Fiebrink听(University of the Arts, London)

Rebecca Fiebrink听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听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鈥檚听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听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听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. Gonz谩lez D铆az, P. Perry, R.听Gibson, B. Martelli, M. Zbyszynski, R. Fiebrink, and M.听Gillies. 2021. 鈥淚nteractML: Making machine learning accessible for creative听practitioners working with movement interaction in immersive media.鈥� In听Proceedings of the 27th ACM Symposium on Virtual Reality Software and听Technology (VRST).

2020. Bernardo, F., M. Zbyszy艅ski, M. Grierson and R. Fiebrink. 2020. 鈥淒esigning and听evaluating the usability of an API for rapid prototyping music technology with听interactive machine learning.鈥澨�Frontiers in Artificial Intelligence听3(13):听1鈥�18.

2019. Fiebrink, R. 2019. 鈥淢achine Learning Education for Artists, Musicians,听and Other Creative Practitioners.鈥澨�ACM Transactions on Machine Learning听Education, Sept 2019. Article No.: 31.

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

2015. Katan, S., M. Grierson, and R. Fiebrink. 2015. 鈥淯sing interactive machine听learning to support interface development through workshops with disabled听people.鈥澨齀n听Proceedings of the听ACM SIGCHI Conference on Human Factors in Computing Systems听(CHI鈥�15).

2011. Fiebrink, R., P. R.听Cook, and D. Trueman. 2011. 鈥淗uman model evaluation in interactive supervised听learning.鈥澨�Proceedings of the听ACM SIGCHI Conference on Human Factors in Computing Systems听(CHI鈥�11).

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

Artemi-Maria Gioti听(University College London)

is a composer and artistic researcher working in the field of artificial intelligence.听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:听

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

Owen Green鈥榮 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 鈥楽onic-Social Genre?: Towards Multimodal Computational Music Genre Modelling鈥� with Georgina Born, Bob Sturm and Melanie Wald-Fuhrmann. 听

Publications

2022. Tremblay, P. A., Roma, G., & Green, O.听Enabling Programmatic Data Mining as Musicking: The Fluid Corpus Manipulation Toolkit.听Computer Music Journal, 45(2), 9鈥�23.听

2018. Bowers, J., & Green, O.听All the Noises: Hijacking Listening Machines for Performative Research.听In T. M. Luke Dahl, Douglas Bowman (Ed.), Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 114鈥�119). Virginia Tech.听

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

2014. Green, O.听NIME, Musicality and Practice-led Methods.听In B. Caramiaux, K. Tahiroglu, R. Fiebrink, & A. Tanaka (Eds.), Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 1鈥�6). Goldsmith鈥檚 University of London.听

2011. Green, O.听Agility and Playfulness: Technology and skill in the performance ecosystem.听Organised Sound, 16(2), 134鈥�144.听听

Christopher Haworth听(University of Birmingham)

Christopher Haworth听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,听The Digital Sociology of Music, which stems from his 2019-21 AHRC Early Career Leadership Fellowship of the same title. Christopher鈥檚 articles have appeared in听Theory Culture Society, Computer Music Journal, Music and Letters, Leonardo Music Journal,听and听Organised Sound, as well as several edited collections. Christopher is also an electronic musician with interests in sound synthesis, spatialisation, and psychoacoustics.

Publications

2022.听鈥淭otal Immersion: Did post-punk and industrial culture zines give us the information dark age?鈥�,听Theory, Culture, Society, 39 (7-8)听(Accepted, publication December 2022).

2021.听鈥淢usic and Cybernetics in Historical Perspective鈥澨�(co-edited with Eric Drott).听听Resonance: Journal of Sound and Culture. California:听 University of California Press.

2020.听鈥淒igital Utopianism in Early Network Music: The Rise and Fall of The Res Rocket Surfer Band鈥澨齀n: Robert Adlington and Esteban Buch (eds),听Finding Democracy in Music, London: Routledge (Musical Cultures of the Twentieth Century series).

2018.听鈥淧rotentions and Retentions of Xenakis and Cage: Nonhuman Actors, Genre and Time in Microsound鈥�,听Contemporary Music Review, 35 (1-2), 606-625.

2017.听鈥淔rom Microsound to Vaporwave: Internet-mediated musics, online methods, and genre.鈥澨齅usic and Letters, 98(4), pp.601-647, joint-authored with Georgina Born (winner of Music and Letters鈥� Annual Westrup Prize for the best article published in the journal)

听

Jenny Judge听(University of Melbourne, Australia)

Jenny Judge听is a Lecturer (i.e. assistant professor) in philosophy at the University of Melbourne. She holds a PhD in philosophy (2022) from New York University and a PhD in music (2016) from the University of Cambridge.听

Judge鈥檚 work explores the resonances between music, the philosophy of mind and normative philosophy broadly construed. Her current research has two strands. The first is the development of a new philosophical theory of musical expression, according to which musical expression is in fact a species of representation. On this view, music turns out to have 鈥榤eaning鈥� in the strict philosophical sense of representational content. And so, a consideration of music promises to augment our understanding of the varieties of representation that exist, and the true scope of what may be represented 鈥� that is, what may be communicated, understood, and indeed thought about at all.

The second strand investigates the impact of digital technology on our moral and aesthetic lives, and on musical experience in particular. Current questions Judge is exploring include: Given the unproblematic existence of unofficial tribute bands, what exactly (if anything) is wrong with using an AI to emulate the style of a living artist without their consent? Do automated recommendation algorithms aid or hinder us in developing our musical taste? And what might the rise of generative AI mean for musicians, for good or ill?

Publications:

forthcoming.听Lessons from an Irish pub: Atmosphere, clutter, and aesthetic (in)attention.听ed. Adams, Z., Meskin, A. and Lehtinen, S. Third Place Aesthetics. New York: Routledge.

2020.听Feeling the beat鈥�: multimodal perception and the experience of rhythm.听ed. Cheyne, P., Hamilton A., and Paddison M. The Philosophy of Rhythm: Aesthetics, Music, Poetics. Oxford: Oxford University Press.

2020. Judge, J. and Nanay, B.听The role of expectations in musical experience.听ed. Levinson J., Nielson N. and McCauley, T. The Oxford Handbook of Western Music and Philosophy. Oxford: Oxford University Press, 2020.

2018.听The surprising thing about musical surprise.听Analysis, 78:2 pp. 225鈥�234.

2016.听Rev. of On Music by Theodore Gracyk.听The British Journal of Aesthetics, 56:3, pp. 325-329.

Judge has also published several pieces in the media, most of which are philosophical critiques of the impact of the Internet on the felt quality of our everyday lives. A selection can be found听.听

She also writes for the programme books of both听Carnegie Hall and the San Francisco Symphony.

Darci Sprengel听(Kings College London)

Darci Sprengel听is a Lecturer in the Music Industry in the department of Culture, Media and the Creative Industries at King鈥檚 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鈥檚 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.听

Publications

Articles:

Under review.听鈥淔rom Grassroots Initiatives to Imperial Lag: Theorizing the Platformisation of the Creative Industries from the Global South.鈥澨�听

Under review.听鈥淩esearch Partnerships between Ethnographers and the Music Tech Industry: Possibilities and Limitations.鈥澨�听

2020.听鈥淩eframing the 鈥楢rab Winter鈥�: The Importance of Sleep and a Quiet Atmosphere after 鈥楧efeated鈥� Revolutions.鈥澨鼵ulture, Theory & Critique 61 (2-3): 246-266.听

2020.听鈥溾�楲oud鈥� and 鈥楺uiet鈥� Politics: Questioning the Role of 鈥榯he Artist鈥� in Street Art Projects after the 2011 Egyptian Revolution.鈥澨齀nternational Journal of Cultural Studies 23 (2): 208-226.听

Book chapters:

In preparation听鈥淒ata Colonization and Its Refusals: The Case of Egypt鈥檚 Independent Music Scenes.鈥澨齀n Digital Platforms in the Global South: Shaping a Critical Approach, edited by Philip Bouquillion, Christina Ithurbide, and Tristan Mattelart. London: Routledge.听

Under review.听鈥淭he Classed, Gendered, and Imperial Politics of Digital Distribution in the Arabic Music Industry.鈥澨齀n The Oxford Handbook to the Global Music Industries, edited by K.E. Goldschmitt and Jayson Beaster-Jones. Oxford: Oxford University Press.听

Under review.听鈥淐urating Tarab on Music Streaming Services: The Cultural Politics of Localization and Algorithmic Bias on Spotify, Anghami, and Deezer.鈥澨齀n 峁琣rab: Music, Ecstasy, Emotion, and Performance, edited by Michael Frishkopf, Dwight Reynolds, and Scott Marcus. Austin: University of Texas Press.

听

Jonathan Sterne听(McGill University)

Jonathan Sterne听teaches in the Department of Art History and Communication Studies at McGill University.听 He is the author of听Diminished Faculties: A Political Phenomenology of Impairment听(Duke 2021);听MP3: The Meaning of a Format听(Duke 2012),听The Audible Past: Cultural Origins of Sound Reproduction听(Duke 2003), and numerous articles on media, technologies and the politics of culture. 听He is also editor of听The Sound Studies Reader听(Routledge 2012) and co-editor of听The Participatory Condition in the Digital Age听(Minnesota 2016). 听He is working on a series of essays on artificial intelligence and culture, and with Mara Mills he is writing听Tuning Time: Histories of Sound and Speed.听Visit his website at听. 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.听Diminished Faculties: A Political Phenomenology of Impairment听(Duke University Press)

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

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

As editor or co-editor:

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

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

2012.听The Sound Studies Reader听(Routledge)听

2021. Co-authored with Elena Razlogova, 鈥�,鈥澨�Cultural Studies听35:2.

2020. Co-authored with Mara Mills, 鈥淪econd Rate: Tempo Regulation, Helium Speech, and 鈥業nformation Overload,鈥欌�澨�Triple Canopy听#26:听

2020. Co-authored with Mara Mills,听,鈥澨�PMLA听(Publications of the Modern Language Association)135:2: 401-411.

2020. 鈥�,鈥澨�Testing Hearing,听eds. Viktoria Traczyk, Mara Mills and Alexandra Hui, 159-185. New York: Oxford University Press.

2019. Co-authored with Elena Razlogova, 鈥�,鈥澨�Social Media + Society听5:2 (April-June): 1-18.

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

Bob L. T. Sturm听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 (), and is probably most known for his work on horses, the GTZAN dataset, and playing Ai generated folk music on his accordion ().

Publications

2021. R. Huang and B. L. T. Sturm,听鈥淩eframing 鈥渁ura鈥�: Authenticity in the application of ai to irish traditional music,鈥澨齣n Proc. AI Music Creativity.

2021. B. L. T. Sturm and O. Ben-Tal, Handbook of Artificial Intelligence for Music, ch.听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 虂omez,听鈥淎rtificial intelligence and music: Open questions of copyright law and engineering praxis,鈥澨齅DPI 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, 鈥淢achine learning research that matters for music creation: A case study,鈥澨齁. New Music Research, vol. 48, no. 1, pp. 36鈥�55.

2014. B. L. Sturm,听鈥淎 survey of evaluation in music genre recognition,鈥澨齣n Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation (A. Nu 虉rnberger, S. Stober, B. Larsen, and M. Detyniecki, eds.), vol. LNCS 8382, pp. 29鈥�66.

2014. B. L. Sturm,听鈥淭he state of the art ten years after a state of the art: Future research in music information retrieval,鈥澨齁. New Music Research, vol. 43, no. 2, pp. 147鈥�172.

2014. B. L. Sturm,听鈥淎 simple method to determine if a music information retrieval system is a 鈥渉orse鈥�,鈥� IEEE Trans. Multimedia, vol. 16, no. 6, pp. 1636鈥�1644

2013. B. L. Sturm,听鈥淐lassification accuracy is not enough: On the evaluation of music genre recognition systems,鈥澨齁. Intell. Info. Systems, vol. 41, no. 3, pp. 371鈥�406.

Advisory Board

Tobias Blanke (University of Amsterdam)
Kate Crawford (USC Annenberg; Microsoft Research)
Bernard Geoghagen (Kings College London)