ECTS credits: 2

 

Course parameters:

Language: English

Level of course: Postgraduate

Time of year: Q3 2024

No. of contact hours/hours in total incl. preparation, assignment(s) or the like: 37/67

Capacity limits: 20 participants

Course fee: No fee, applications competitive

 

Objectives of the course:

This course is aimed at a growing cohort of postgraduate data scientists and biologists who use automated methods to study insects (and other arthropods) in their research. Participants will be introduced to the state-of-the-art when it comes to automated monitoring of insects, including various modes of image acquisition, their strengths and weaknesses, approaches to image annotation and data management, and models to automatically extract biological information from sensor-derived media such as images and sounds.

 

Learning outcomes and competences:

At the end of the course, the student should be able to:

• Plan and communicate a project using automated monitoring to address important questions in entomology.
• Select appropriate automated monitoring methods based on strengths, weaknesses, and data requirements.
• Design a data acquisition program using autonomous sensors, especially cameras, with special attention to hardware design, deployment, and scheduling.
• Generate labeled datasets for analysis or model training using strategic manual annotation.
• Manage data appropriately with reference to metadata standards.
• Train models to detect, classify or characterize insects in images.
• Deploy open-source models to achieve research goals, with careful consideration of domain shifts and model uncertainty.

 

Compulsory programme:

 

Course contents:

Participants will achieve their learning outcomes through a combination of case-based learning, delivered in the form of guest lectures and workshops from international experts, and project-based learning with a focus on presentation and interaction with peers. Participants will be strategically arranged into teams (based on complementary interests) before the summer school and will carry out up to 30h of preparation before they travel to the venue. During the summer school they will co-develop research projects, which they will iteratively present to their peers and receive constructive feedback. Finally, participants' experiences will be grounded in reality through multiple hardware demonstrations, especially under field conditions, in the Mols Bjerge National Park.

 

Prerequisites:

None

 

Name of lecturers:

Jamie Alison, Quentin Geissmann, Toke Høye, Jarrett Blair, Charlie Outhwaite, James Crall, Hjalte Mann, Jenna Lawson, Luca Pegoraro

 

Type of course/teaching methods:

Lectures, workshops, field demonstrations, group work

 

Literature:

None

 

Course homepage:

https://darsa.info/ACCESS-2024/

 

Course assessment:

Success is determined based on a final project proposal document and a presentation of the proposal

 

Provider:

Department of Ecoscience and the Centre for Quantitative Genetics and Genomics

 

Special comments on this course:

The course provides free accommodation and food for the selected candidates, but travel to and from the venue must be covered by the participants or their institutions. In 2024 the course is funded by the Danish Ministry of Higher Education and Science though a Global Innovation Network Program grant on Automated Monitoring of Insects.

 

Time:

30 September to 4 October 2024

 

Place:

Mols laboratory research station, near Aarhus, Denmark

 

Course fee:

No fee, applications competetive

 

Registration:

To complete your application, please fill out the application form by 15 April 2024.

If you have any questions, please contact Quentin Geissmann: qgeissmann@qgg.au.dk