Justin Le Louëdec ☀️ 🤖

With a background in computer science, focusing on computer vision and machine learning applied to robotics and agronomy, my previous work involved developing tools for object detection, segmentation, and 3D reconstruction to support applications such as autonomous harvesting, plant phenotyping, and yield prediction. I am now applying these skills to the field of space weather, where I focus on the segmentation, detection, and 3D modelling of coronal mass ejections (CMEs). My core interest lies in understanding the shape, structure, and propagation of complex objects—whether they are fruits, plants, or solar eruptions—in order to support better modelling, forecasting, and decision-making across disciplines. I aim to develop tools and models that help robots and other researchers across domains improve their understanding, predictions, and operational outcomes.

📢📢 Looking for a new position/job in ML, computer vision, space weather or cool other application. Get it touch

Research Interests

3D Vision, Machine learning, Space Weather, Robotics

News

[07/2025]: First paper in Space Weather: Beacon2science
[06/2023]: I joined the Austrian Space Weather Office as postdoctoral researcher
[11/2022]: PhD thesis Submitted

Recent research

See all research

Beacon2Science: Enhancing STEREO/HI beacon data with machine learning for efficient CME tracking

Justin Le Louëdec, Maike Bauer, Tanja Amerstorfer, Jackie A Davies

Paper Code

In Space Weather
2025
Deep learning investigation for chess player attention prediction using eye-tracking and game data

Justin Le Louëdec, Thomas Guntz, James L Crowley, Dominique Vaufreydaz

Paper

In Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications}
2019
Solar Transient Recognition Using Deep Learning (STRUDL) for heliospheric imager data

Maike Bauer, Justin Le Louëdec, Tanja Amerstorfer, Luke Barnard, David Barnes, Helmut Lammer

Paper

Accepted in Space Weather
2025