Mark Cartwright
Mark Cartwright
Assistant Professor, Informatics
3902E Guttenberg Information Technologies Center (GITC)
About Me
Mark Cartwright is an Assistant Professor of Informatics at New Jersey Institute of Technology where he leads the Sound Interaction and Computing (SInC) Lab. His research lies at the intersection of human-computer interaction and machine learning applied to audio and music. Specifically, he researches human-centered machine listening and audio processing tools that enable new interactions for creative expression through sound and understanding the acoustic world at scale. Before his current position, he was a research assistant professor at NYU affiliated with both the Music and Audio Research Laboratory and the Center for Urban Science and Progress. He received his PhD in Computer Science at Northwestern University as a member of the Interactive Audio Lab, and he holds an MA in Music Science and Technology from Stanford University (CCRMA) and a BMus in Music Technology from Northwestern University.
Education
Ph.D.; Northwestern University; Computer Science; 2016
M.A.; Stanford University; Music Science and Technology; 2007
B.M.; Northwestern University; Music Technology; 2004
M.A.; Stanford University; Music Science and Technology; 2007
B.M.; Northwestern University; Music Technology; 2004
Website
2025 Spring Courses
IS 488 - INDEPENDENT STUDY IN INFO
IS 701B - MASTER'S THESIS
IS 726 - INDEPENDENT STUDY II
IS 665 - DATA ANALYTICS FOR INFO SYSTEM
IS 776 - IS RESEARCH STUDY
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 700B - MASTER'S PROJECT
IS 725 - INDEPENDENT STUDY I
IS 701B - MASTER'S THESIS
IS 726 - INDEPENDENT STUDY II
IS 665 - DATA ANALYTICS FOR INFO SYSTEM
IS 776 - IS RESEARCH STUDY
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 700B - MASTER'S PROJECT
IS 725 - INDEPENDENT STUDY I
Teaching Interests
machine listening, interactive machine learning, audio processing, multimedia computing
Past Courses
CS 485: SELECTED TOPICS IN CS
CS 485: ST: MACHINE LISTENING
CS 698: ST: MACHINE LISTENING
IS 247: DESIGNING THE USER EXPERIENCE
IS 485: SPECIAL TOPICS IN INFORMATION SYSTEMS
IS 485: SPECIAL TOPICS IN IS - I
IS 485: ST: MACHINE LISTENING
IS 657: SPATIOTEMPORAL URBAN ANALYTICS
IS 698: ST: SPECIAL PROJECTS
CS 485: ST: MACHINE LISTENING
CS 698: ST: MACHINE LISTENING
IS 247: DESIGNING THE USER EXPERIENCE
IS 485: SPECIAL TOPICS IN INFORMATION SYSTEMS
IS 485: SPECIAL TOPICS IN IS - I
IS 485: ST: MACHINE LISTENING
IS 657: SPATIOTEMPORAL URBAN ANALYTICS
IS 698: ST: SPECIAL PROJECTS
Research Interests
machine listening, human-computer interaction, machine learning, audio, music, crowdsourcing, human-AI interaction, creativity support tools, interactive machine learning, music information retrieval, digital signal processing, sound accessibility
Conference Paper
“Towards a Rich Format for Closed-Captioning”
Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), October (4th Quarter/Autumn) 2024.
Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), October (4th Quarter/Autumn) 2024.
Journal Article
Elly Knight, Tessa Rhinehart, Devin R de Zwaan, Matthew J Weldy, Mark Cartwright, Scott Hawley, Jeffrey Larkin, Damon Lesmeister, Erin Bayne, Justin Kitzes. “Individual Identification in Acoustic Recording.” Trends in Ecology and Evolution.
Ana Mendez Mendez, Mark Cartwright, Juan Pablo Bello, Oded Nov. 2022. “Eliciting Confidence for Improving Crowdsourced Audio Annotations.” ACM, vol. 6, no. CSCW1.
Bryan Pardo, Mark Cartwright, Prem Seetharaman, Bongjun Kim. 2019. “Learning to Build Natural Audio Production Interfaces.” Arts, vol. 8, no. 3, pp. 110.
Brian McFee, Jong Wook Kim, Mark Cartwright, Justin Salamon, Rachel M. Bittner, Juan Pablo Bello. 2019. “Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research.” IEEE Signal Processing Magazine, vol. 36, no. 1, pp. 128--137.
Vincent Lostanlen, Justin Salamon, Mark Cartwright, Brian McFee, Andrew Farnsworth, Steve Kelling, Juan Pablo Bello. 2019. “Per-Channel Energy Normalization: Why and How.” IEEE Signal Processing Letters, vol. 26, no. 1, pp. 39--43.
Mark Cartwright, Ayanna Seals, Justin Salamon, Alex Williams, Stephanie Mikloska, Duncan MacConnell, Edith Law, Juan Pablo Bello, Oded Nov. 2017. “Seeing Sound: Investigating the Effects of Visualizations and Complexity on Crowdsourced Audio Annotations.” .
Ana Mendez Mendez, Mark Cartwright, Juan Pablo Bello, Oded Nov. 2022. “Eliciting Confidence for Improving Crowdsourced Audio Annotations.” ACM, vol. 6, no. CSCW1.
Bryan Pardo, Mark Cartwright, Prem Seetharaman, Bongjun Kim. 2019. “Learning to Build Natural Audio Production Interfaces.” Arts, vol. 8, no. 3, pp. 110.
Brian McFee, Jong Wook Kim, Mark Cartwright, Justin Salamon, Rachel M. Bittner, Juan Pablo Bello. 2019. “Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research.” IEEE Signal Processing Magazine, vol. 36, no. 1, pp. 128--137.
Vincent Lostanlen, Justin Salamon, Mark Cartwright, Brian McFee, Andrew Farnsworth, Steve Kelling, Juan Pablo Bello. 2019. “Per-Channel Energy Normalization: Why and How.” IEEE Signal Processing Letters, vol. 26, no. 1, pp. 39--43.
Mark Cartwright, Ayanna Seals, Justin Salamon, Alex Williams, Stephanie Mikloska, Duncan MacConnell, Edith Law, Juan Pablo Bello, Oded Nov. 2017. “Seeing Sound: Investigating the Effects of Visualizations and Complexity on Crowdsourced Audio Annotations.” .
Conference Proceeding
“Multi-label Open-set Audio Classification”
Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), September 2023.
“Does a quieter city mean fewer complaints? The Sounds of New York City During COVID-19 Lockdown”
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2023.
“A Study on Robustness to Perturbations for Representations of Environmental Sound”
August 2022.
“Urban Rhapsody: Large-scale exploration of urban soundscapes”
June 2022.
“How people who are deaf, Deaf, and hard of hearing use technology in creative sound activities”
ACM, October (4th Quarter/Autumn) 2022.
Proceedings of the Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), September 2023.
“Does a quieter city mean fewer complaints? The Sounds of New York City During COVID-19 Lockdown”
Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2023.
“A Study on Robustness to Perturbations for Representations of Environmental Sound”
August 2022.
“Urban Rhapsody: Large-scale exploration of urban soundscapes”
June 2022.
“How people who are deaf, Deaf, and hard of hearing use technology in creative sound activities”
ACM, October (4th Quarter/Autumn) 2022.
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Conference Abstract
“A retrospective on monitoring noise pollution with machine learning in the Sounds of New York City project”
Journal of the Acoustical Society of America, May 2023.
Journal of the Acoustical Society of America, May 2023.