The DARSA Group

The DARSA Group

Digital Approaches for Resilient and Sustainable Agriculture

Aarhus University

Center for Quantitative Genetics and Genomics

About us

The Digital Approaches for Resilient and Sustainable Agriculture (DARSA) group is part of the Center for Quantitative Genetics and Genomics (QGG), at Aarhus University. Within DARSA, we develop and apply remote-sensing tools and innovative open-source machine-learning methods to make agroecosystems more productive, sustainable and resilient. We collaborate with other members of the QGG as well as with other researchers in Aarhus and worldwide to target both the breeding and production sides of agriculture. Amid severe environmental crises, we aim to lead a new, digital and sustainable, green transition. The DARSA group recently started, and we are actively looking for collaborators and new members, so do not hesitate to contact us.

Interests
  • 🧠 Development of Deep-Learning Tools
  • 🐛 Automatic Monitoring of Agricultural Pests
  • 🌱 High-Throughput Plant Phenotyping
  • 🌳 Agroecology and Biodiversity

People

To discuss opportunities to join the group, do not hesitate to send us a CV and describe your interest.

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All Principal Investigator Postdoc PhD Student Master Student
Sep 1, 2022
Quentin Geissmann
Quentin Geissmann

Principal Investigator
Follow ORCID Github RG
Aug 1, 2024
Helena Russello
Helena Russello

Postdoc
ORCID Github
Dec 1, 2023
Marta Gomez
Marta Gomez

PhD Student
ORCID Github
Jun 1, 2023
Melika Baghooee
Melika Baghooee

PhD Student
ORCID Github
Sep 1, 2022
Daphne Chevalier
Daphne Chevalier

Master Student
ORCID Github

Projects

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All Insects Agroecology Microbio. Deep Learning Hardware Software Ongoing Former
Nov 29, 2023
ANTENNA
ANTENNA

MAkiNg Technology work for moNitoring polliNAtors
Nov 28, 2023
Global Worming
Global Worming

Monitoring earthworms with AI and remote sensing
Feb 15, 2021
Sticky Pi
Sticky Pi

An AI-powered smart insect trap for community chronoecology
Jan 11, 2015
Ethoscope
Ethoscope

A platform to monitor behaviour of small animals in real-time
Jan 21, 2013
OpenCFU
OpenCFU

An open-source software to count bacterial colonies

Publications

As of 2022, these are selected publications from Quentin Geissmann’s related previous work.

Year Title Journal Authors
2024 Machine learning reveals singing rhythms of male Pacific field crickets are clock controlled Behavioral Ecology Westwood et al.
2023 Hierarchical classification of insects with multitask learning and anomaly detection Ecological Informatics Bjerge et al.
2022 Sticky Pi is a high-frequency smart trap that enables the study of insect circadian activity under natural conditions PLOS Biology Geissmann et al.
2019 Most sleep does not serve a vital function: Evidence from Drosophila melanogaster Science Advances Geissmann et al.
2019 Rethomics: An R framework to analyse high-throughput behavioural data PLOS ONE Geissmann et al.
2017 Ethoscopes: An open platform for high-throughput ethomics PLOS Biology Geissmann et al.
2013 OpenCFU, a New Free and Open-Source Software to Count Cell Colonies and Other Circular Objects PLOS ONE Geissmann
2009 Meta-phenomics: Building a unified framework for interpreting plant growth responses to diverse environmental variables Comparative Biochemistry and Physiology, Part A Hendrik Poorter et al.

Collaborators

QGG
The Center for Quantitative Genetics and Genomics at Aarhus University, Denmark.
Sep 1, 2022
QGG
Høye Lab
The Høye Lab at Aarhus University, Denmark.
Sep 1, 2022
PIEE Lab
The Plant-Insect Ecology and Evolution Lab at UBC, Canada.
Sep 1, 2022
PIEE Lab

Contact