Mark Cartwright

Assistant Professor, Informatics
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.
Ph.D.; Northwestern University; Computer Science; 2016
M.A.; Stanford University; Music Science and Technology; 2007
B.M.; Northwestern University; Music Technology; 2004
CS 488 - INDEPENDENT STUDY IN CS
CS 726 - INDEPENDENT STUDY II
IS 488 - INDEPENDENT STUDY IN INFO
IS 701B - MASTER'S THESIS
IS 726 - INDEPENDENT STUDY II
CS 489 - COMPUTER SCIENCE RESEARCH PROJ
CS 701B - MASTER'S THESIS
CS 725 - INDEPENDENT STUDY I
IS 491 - SENIOR PROJECT - IS
IS 665 - DATA ANALYTICS FOR INFO SYSTEM
IS 776 - IS RESEARCH STUDY
IS 790A - DOCT DISSERTATION & RES
IS 792 - PRE-DOCTORAL RESEARCH
IT 488 - INDEPENDENT STUDY
IS 465 - ADVANCED INFORMATION SYSTEMS
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 700B - MASTER'S PROJECT
CS 700B - MASTER'S PROJECT
CS 790A - DOCT DISSERTATION & RES
CS 792 - PRE-DOCTORAL RESEARCH
IS 725 - INDEPENDENT STUDY I
machine listening, interactive machine learning, audio processing, multimedia computing
CS 485: SELECTED TOPICS IN CS
CS 485: ST: MACHINE LISTENING
CS 698: ST: MACHINE LISTENING
IS 247: DESIGNING THE USER EXPERIENCE
IS 465: ADVANCED INFORMATION SYSTEMS
IS 465: DATA ANALYTICS FOR BUSINESS INFORMATION SYSTEMS
IS 485: SPECIAL TOPICS IN INFORMATION SYSTEMS
IS 485: SPECIAL TOPICS IN IS - I
IS 485: ST: MACHINE LISTENING
IS 657: SPATIOTEMPORAL URBAN ANALYTICS
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
Lloyd May, Michael Clemens, Khang Dang, Keita Ohshiro, Sripathi Sridhar, Pauline Wee, Magdalena Fuentes, Sooyeon Lee, Mark Cartwright. 2025. "“Choices? That's the dream”: challenges and opportunities in non-speech information closed-captioning." Frontiers in Computer Science, vol. 7.
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.
"Audio Engineering for Podcasts by deaf and Hard of Hearing Creators"
ACM, April (2nd Quarter/Spring), 2025.
"Audio Engineering by People Who Are deaf and Hard of Hearing: Balancing Confidence and Limitations"
ACM, May, 2024.
"Unspoken Sound: Identifying Trends in Non-Speech Audio Captioning on YouTube"
ACM, May, 2024.
"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.
"Towards a Rich Format for Closed-Captioning"
Proceedings of the ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), October (4th Quarter/Autumn), 2024.
"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.