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
2024 Fall Courses
IS 488 - INDEPENDENT STUDY IN INFO
IS 701B - MASTER'S THESIS
IS 726 - INDEPENDENT STUDY II
IS 776 - IS RESEARCH STUDY
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
IS 465 - ADVANCED INFORMATION SYSTEMS
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 776 - IS RESEARCH STUDY
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
IS 465 - ADVANCED INFORMATION SYSTEMS
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
Knight, Elly, & Rhinehart, Tessa, & de Zwaan, Devin R, & Weldy, Matthew J, & Cartwright, Mark, & Hawley, Scott, & Larkin, Jeffrey, & Lesmeister, Damon, & Bayne, Erin, & Kitzes, Justin Individual Identification in Acoustic Recording. Trends in Ecology and Evolution,
Mendez Mendez, Ana , & Cartwright, Mark, & Bello, Juan Pablo, & Nov, Oded (2022). Eliciting Confidence for Improving Crowdsourced Audio Annotations. ACM, 6(CSCW1),
Pardo, Bryan, & Cartwright, Mark, & Seetharaman, Prem, & Kim, Bongjun (2019). Learning to Build Natural Audio Production Interfaces. Arts, 8(3), 110.
McFee, Brian, & Kim, Jong Wook, & Cartwright, Mark, & Salamon, Justin, & Bittner, Rachel M., & Bello, Juan Pablo (2019). Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research. IEEE Signal Processing Magazine, 36(1), 128--137.
Lostanlen, Vincent, & Salamon, Justin, & Cartwright, Mark, & McFee, Brian, & Farnsworth, Andrew, & Kelling, Steve, & Bello, Juan Pablo (2019). Per-Channel Energy Normalization: Why and How. IEEE Signal Processing Letters, 26(1), 39--43.
Cartwright, Mark, & Seals, Ayanna, & Salamon, Justin, & Williams, Alex, & Mikloska, Stephanie, & MacConnell, Duncan, & Law, Edith, & Bello, Juan Pablo, & Nov, Oded (2017). Seeing Sound: Investigating the Effects of Visualizations and Complexity on Crowdsourced Audio Annotations.
Mendez Mendez, Ana , & Cartwright, Mark, & Bello, Juan Pablo, & Nov, Oded (2022). Eliciting Confidence for Improving Crowdsourced Audio Annotations. ACM, 6(CSCW1),
Pardo, Bryan, & Cartwright, Mark, & Seetharaman, Prem, & Kim, Bongjun (2019). Learning to Build Natural Audio Production Interfaces. Arts, 8(3), 110.
McFee, Brian, & Kim, Jong Wook, & Cartwright, Mark, & Salamon, Justin, & Bittner, Rachel M., & Bello, Juan Pablo (2019). Open-Source Practices for Music Signal Processing Research: Recommendations for Transparent, Sustainable, and Reproducible Audio Research. IEEE Signal Processing Magazine, 36(1), 128--137.
Lostanlen, Vincent, & Salamon, Justin, & Cartwright, Mark, & McFee, Brian, & Farnsworth, Andrew, & Kelling, Steve, & Bello, Juan Pablo (2019). Per-Channel Energy Normalization: Why and How. IEEE Signal Processing Letters, 26(1), 39--43.
Cartwright, Mark, & Seals, Ayanna, & Salamon, Justin, & Williams, Alex, & Mikloska, Stephanie, & MacConnell, Duncan, & Law, Edith, & Bello, Juan Pablo, & Nov, Oded (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