2026-05-19 –, Jeanne Roos
In this presentation you will learn about practical use cases of applying AI in the domain of HAS green academy.
HAS green academy, with 3.000+ students the biggest HBO green school in The Netherlands, started last year with a new research group. The name of this research group is "Data Intelligence for Sustainable Transitions". The group consists of +/- 10 researchers with a solid background in applied biology, geography, ecology, food technology and agriculture.
With this new group, HAS green academy aims to provide a powerful impulse to research on how spatial data intelligence can deliver added value to the sustainable transitions of our living environment. These transitions contribute significantly to climate adaptation, energy transition, and biodiversity in both urban and rural areas.
The research group focuses on the core areas Knowledge Modeling, Remote Sensing, Digital Twins, AI and Data & Ethics.
Policy makers (in the green domain), researchers, students
What is the key take away of your session?:Nature and technology (AI) have far more connections than most people know
“Data” has been the common thread throughout the career of Harm Bodewes: data modelling, data science, data warehouses, data lakes, (master) data management and data mesh are his main areas of interest. Harm advises organisations, teaches courses and gives presentations, writes blog posts and contributes to the podcast De Dataloog.
In December 2024, he was appointed Lector of Data Intelligence for Sustainable Transitions at HAS green academy. The research group investigates how technology can contribute to sustainable solutions in agriculture, food and the living environment, and connects these domains through artificial intelligence, data‑driven knowledge and applications. More information about the research group: https://www.has.nl/en/research/professorships/data-intelligence-for-sustainable-transitions-professorship/
I build scalable, open-source data ecosystems designed for complex transitions in agriculture and sustainability. With a background in Applied Data Science and Computer Vision, I focus on bridging the gap between high-level strategy and robust technical implementation.
My work at HAS green academy involves designing cloud-agnostic architectures that prioritize interoperability and transparency. I advocate for reproducible workflows and open standards over proprietary lock-ins.
Technical Focus:
- Engineering: Python, Airflow, Docker, PostgreSQL.
- Applied AI: Computer Vision (Animal Behavior), LLMs, Machine Learning Engineering.
- Data Management: CKAN, Open Metadata Standards, Sensor Data Integration.
- Domain Expertise: Sustainable Transitions, Agriculture, Learning Analytics.