I am an applied Visual AI and Computer Vision scientist within the Digital Production group, where I focus on developing and deploying machine-learning–based visual systems to support agricultural research and practice. My work now centers primarily on computer vision and visual intelligence, ranging from hands-on implementation to managing project portfolios and coordinating small teams dedicated to solving agricultural problems with AI-driven visual technologies.

Background:

I graduated as a biomedical engineer and then pursued a PhD in visual neuroscience then worked as an ajducnt professor for a few years in French and Lebanese universities. Since 2020, I joined Agroscope and started working as a data scientist. Since 2022, I work as an applied Visual AI sientist within the Digital Production group, contributing to several projects at the intersection of data engineering, machine learning, and domain-specific agricultural research. Data science covers a broad spectrum of activities and brings challenges stemming from:

The abundance and rapid evolution of tools and frameworks
The need to acquire domain knowledge outside one’s core expertise
The requirement for reproducible, scalable, and generalizable models and systems
My earlier role focused on navigating these challenges by supporting data and machine learning components in multiple projects. While these experiences continue to inform my work, my main focus has now shifted toward computer vision and visual AI.

Project Leadership:
In the work program 2022–2025, I led the Computer Vision Coordination project (SFF11 subproject), aimed at enabling and fostering computer-vision-based research at Agroscope. This involved supporting active CV projects, providing methodological guidance, and organizing workshops and meetings to build a strong internal CV community.

Currently, I am the project lead for IMAGINE, where I oversee the development and integration of next-generation visual AI solutions for agricultural applications.

Funds:

2024 - NOSTRADAMUS (EU project): 700K.
2025 - ETHIC (OFAG): 560K
2025 - Scientific Exchange (SNF): 18k
Examples of Current and Past Contributions

Computer Vision Coordination Project (Project Lead): Coordinated and supported CV-based research across Agroscope; organized technical exchanges and fostered collaboration.
IMAGINE Project (Project Lead)
Rumex Detection Using Computer Vision: Developed the computer vision models and contributed to the system architecture for automated Rumex plant detection.
Smart Irrigation Using Dendrometer Signals over LoRaWAN (previous data science role):  implemented backend automation routines.
Rhythmicity as Welfare Indicators for Ruminants (previous data science role): Developed algorithms in the DigiRhythm package and analyzed rhythmicity data for potential welfare indicators.
 

Google Scholar | ORCID | Linkedin | DigiRhythm Libray | Smart weed control | Github