Author

Thomas A. O’Shea-Wheller

University of ExeterORCID 0000-0002-5537-2659Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell-cell communication· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1

Frequent Co-Authors

Davide M. DominoniiD· 1 shared James A. M. GallowayiD· 1 shared Jolyon T. TrosciankoiD· 1 shared Kevin J. GastoniD· 1 shared Rolando Rodríguez‐MuñoziD· 1 shared Ruonan LiiD· 1 shared Tom TregenzaiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 9 mutual co-author links

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1 shared paperEcology

Davide M. DominoniORCID

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2 papers

Recent·Most cited

EcologybioRxivPreprintJun 19, 2026

Deep learning reveals the individual-level effects of artificial light at night on a wild insect

Ruonan Li, Rolando Rodríguez‐Muñoz, Davide M. Dominoni…·Thomas A. O’Shea-Wheller

This study uses deep learning to analyze individual insect behavior under artificial light at night, finding no effect on broad activity trends but significant changes in fine-scale behavior.

DOI 10.64898/2026.06.15.732354

imagingdeep learning

𝕏 PostBluesky

EcologybioRxivPreprintNov 4, 2025

BehaveAI: a framework for rapidly detecting and classifying objects and behaviour from motion

Jolyon T. Troscianko, Thomas A. O’Shea-Wheller, James A. M. Galloway, Kevin J. Gaston

BehaveAI detects and classifies objects and behaviors from motion using a color-from-motion encoding strategy, enabling efficient and accurate analysis with minimal annotation effort.

1 citation

imagingdeep learning

𝕏 PostBluesky