Preprints:

• Maddie Cusimano, Luke B. Hewitt, Josh H. McDermott. (2023). Bayesian auditory scene synthesis explains human perception of illusions and everyday sounds. bioRxiv; doi: https://doi.org/10.1101/2023.04.27.538626. Project webpage
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Peer-reviewed contributions:

• Agarwal, V., Cusimano, M., Traer, J., & McDermott, J. H. (2021). Object-based synthesis of scraping and rolling sounds based on non-linear physical constraints. Proceedings of the 24th International Conference on Digital Audio Effects.
• Traer, J., Cusimano, M. & McDermott, J. H. (2019). A perceptually inspired generative model of rigid-body contact sounds. Proceedings of the 22nd International Conference on Digital Audio Effects, selected as a talk. (Also presented at CogSci 2019.)
• Cusimano, M., Hewitt, L., Tenenbaum, J. B., & McDermott, J. H. (2018). Auditory scene analysis as Bayesian inference in sound source models. Proceedings of the 40th Annual Conference of the Cognitive Science Society, selected as a talk. (Also presented at CCN 2018, SANE 2018, ProbProg 2018, ARO 2019.)
• Alain, C., Cusimano, M., Garami, L., Backer, K., Habelt, B., Chan, V. & Hasher, L. (2018). Age-related differences in orienting attention to sound object representations. Neurobiology of Aging, 66, 1-11.

My thesis:

• Cusimano, M. (2022). Listening with generative models (Doctoral dissertation, Massachusetts Institute of Technology)

Other contributions:

• Cusimano, M., & McDermott, J. (2017). Sensitivity to physical regularities in auditory event sequences. Association for Research in Otolaryngology Conference (p.580), selected as a poster. (Also presented at ASA 2017.)
• Hu, J., Traer, J., Cusimano, M., & McDermott, J. (2019). Separating object resonance and room reverberation in impact sounds. Talk at CogSci 2019.