Author

Q. Geissmann

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 2 Animal Behavior & Cognition· 1 Plant Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:Drosophila· 2 Approach:experimental assay· 2 Assay:imaging· 2 Organism:Arabidopsis· 1 Assay:behavioral assay· 1 Research Focus:clustering· 1

Frequent Co-Authors

C. H. Haney· 2 shared A. J. Wilson· 1 shared A. R. Jamasb· 1 shared A. S. French· 1 shared D. Thoms· 1 shared D. Wu· 1 shared E. J. Beckwith· 1 shared G. F. Gilestro· 1 shared

Activity by Year

2017-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 11 mutual co-author links

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2 shared papersEcology

C. H. Haney

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection

K. Bjerge, Q. Geissmann, J. Alison, H. M. R. Mann, T. T. Hoye, M. Dyrmann, H. Karstoft

This paper presents an algorithm for hierarchical insect classification using multitask learning and anomaly detection, improving accuracy at higher taxonomic ranks while identifying classification uncertainty.

bioRxiv · Jun 29, 2023Ecology

Sticky Pi, an AI-powered smart insect trap for community chronoecology

Q. Geissmann, P. K. Abram, D. Wu, C. H. Haney, J. Carrillo

The Sticky Pi trap uses AI to monitor insect activity patterns, revealing daily rhythms and community temporal niches without targeting specific species.

PLOS Biology · Jul 7, 2022Peer-reviewedEcology

Loss of a plant receptor kinase recruits beneficial rhizosphere-associated Pseudomonas

Y. Song, A. J. Wilson, X.-C. Zhang, D. Thoms, R. Sohrabi, S. Song, Q. Geissmann, Y. Liu, L. Walgren, S. Y. He, C. H. Haney

This study identifies FERONIA kinase's role in regulating NADPH oxidase to control rhizosphere Pseudomonas levels in Arabidopsis.

bioRxiv · Nov 2, 2020Plant Biology

Ethoscopes: An Open Platform For High-Throughput Ethomics

Q. Geissmann, L. Garcia Rodriguez, E. J. Beckwith, A. S. French, A. R. Jamasb, G. F. Gilestro

Ethoscopes provide an open-source, scalable platform for high-throughput behavioral analysis in Drosophila using real-time machine learning tracking and stimulus delivery.

bioRxiv · Aug 5, 2017Animal Behavior & Cognition