I am a PhD candidate with a background in Geomatics and Remote Sensing.

In my current research, I develop geospatial deep learning algorithms to map marine oil slicks from satellite remote sensing, primarily SAR. Progress on this notoriously challenging task will enable new analyses of natural oil seepage systems which have important environmental implications at the basin scale (e.g. hydrocarbon migration, geological storage).

I recently gave radio interviews in French on the Canadian public broadcaster (here and here), and on the local radio (here), to speak about our recent discovery of an episodic hydrocarbon seep. This news was also covered by national newspapers in Canada (Fr / En).

I regularly take part in scientific conferences. In 2026, I presented our ongoing research at IGARSS and the ISPRS congress.

Universitetet i Bergen

Teaching Assistant 

• GEOV205: Geographic Information Systems - Theory and Practice
• GEOV316: Practical Skills in Remote Sensing and Spatial analysis

Université de Montréal

Teaching Assistant

• GEO1542: Introduction to remote sensing
• GEO3015: Geographic information systems III 
• GEO3532: Spatial modeling
• GEO6341: Complex socio-ecological systems modeling
• GEO6343: Advanced remote sensing

 

Academic article

• Julien Vadnais; Christian Haug Eide; Nicolas Pinet et al. (2026). Origin and fate of an episodic oil seep, Gulf of St. Lawrence (Canada). (external link)
• Julien Vadnais; Benjamin Aubrey Robson; Christian Haug Eide et al. (2025). Transfer learning between Sentinel-1 acquisition modes enhances the few-shot segmentation of natural oil slicks in the Arctic. (external link)

Conference lecture

• Julien Vadnais (2026). TH2.R11: Remote sensing for Oil & Gas Exploration, Production and Environmental Monitoring. (external link)
• Julien Vadnais; Christian Haug Eide; Benjamin Aubrey Robson (2025). Advanced geomatics and machine learning to map and study spatio-temporal patterns of natural hydrocarbon seepage in the North Sea. (external link)
• Julien Vadnais; Benjamin Aubrey Robson; Christian Haug Eide (2025). On the Challenge of Oil Slick Lookalikes in SAR mapping: Transfer Learning With Limited Labels. (external link)

See a complete overview of publications in NVA.