Author

Maddie Cusimano

Massachusetts Institute of TechnologyORCID 0000-0002-7435-2434Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Animal Behavior & Cognition· 1 Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Organism:chicken / avian· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:phylogenetics / evolution· 1

Frequent Co-Authors

Benjamin HoffmaniD· 2 shared David RobinsoniD· 2 shared Emmanuel ChemlaiD· 2 shared Logan S. JamesiD· 2 shared Marius MarioniD· 2 shared Matthieu GeistiD· 2 shared Milad AlizadehiD· 2 shared Sara C. KeeniD· 2 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

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2 shared papersBioinformatics

Benjamin HoffmanORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BirdCODE: Detecting bird communication at scale

Anthony Fine, Benjamin Hoffman, David Robinson, Marius Miron, Milad Alizadeh, Emmanuel Chemla, Maddie Cusimano, Logan S. James, Sara C. Keen, Emma Matthies, Gagan Narula, Inês Nolasco, Matthieu Geist

BirdCODE detects and classifies bird vocalizations from large audio datasets, enabling large-scale studies of bird communication with improved temporal resolution and species coverage.

bioRxiv · Aug 5, 2026 · PreprintBioinformatics

Repertoire-behavior mapping reveals signal functions in cooperatively breeding crows

Maddie Cusimano, Benjamin Hoffman, Carlos Guzón-García, Angela Mcenerey, Margaret Bezrutczyk, Jen-Yu Liu, Logan S. James, Sara C. Keen, Louis Mahon, Olivier Pietquin, Milad Alizadeh, Damián Ezequiel Blasi, Matthieu Geist, Marius Marion, David Robinson, , Daniela Canestrari

The paper maps vocal repertoires to social behaviors in cooperative crows using machine learning and audio-visual data.

bioRxiv · May 4, 2026 · PreprintAnimal Behavior & Cognition

Listening with generative models

Maddie Cusimano, Luke Hewitt, Josh H. McDermott

This study uses generative models to explain auditory perception, showing they can account for illusions and real-world sounds with human-like organization.

Cognition · Aug 30, 2024Peer-reviewedNeuroscience