Author

Joel Kowalewski

University of California, RiversideORCID 0000-0002-7060-7890Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Animal Behavior & Cognition· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Organism:human· 2 Assay:CITE-seq· 1 Approach:deep learning· 1 Organism:Drosophila· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1

Frequent Co-Authors

Anandasankar RayiD· 2 shared Barbara F Baer-ImhoofiD· 1 shared Boris BaeriD· 1 shared Jadrian Ejercito· 1 shared Matthew Luy· 1 shared Payton DePalmaiD· 1 shared Ryan S. ArvidsoniD· 1 shared Sean M. Boyle· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 21 mutual co-author links

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2 shared papersAnimal Behavior & Cognition

Anandasankar RayORCID

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2 papers

Recent·Most cited

Animal Behavior & CognitioneLifePeer-reviewedSep 23, 2026

Machine learning of honey bee olfactory behavior identifies repellent odorants in free flying bees in the field

Joel Kowalewski, Barbara F Baer-Imhoof, Tom Guda…·Anandasankar Ray

The paper uses machine learning to identify repellent odorants for honey bees, validated in both lab and field settings, showing potential for pesticide mitigation.

DOI 10.7554/elife.104831.3

humandeep learning

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NeurosciencebioRxivPreprintDec 25, 2023

Machine Learning Based Modelling of Human and Insect Olfaction Screens Millions of compounds to Identify Pleasant Smelling Insect Repellents

Joel Kowalewski, Sean M. Boyle, Ryan S. Arvidson…·Anandasankar Ray

The paper uses machine learning to predict odor valence in humans and insects, screening millions of compounds to identify pleasant-smelling insect repellents.

1 citation

humanDrosophila

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