About me

🔬 About My Research

I work at the Norwegian Institute for Nature Research (NINA) 🇳🇴, where I develop and apply AI methods to improve biodiversity monitoring. My work centers on 🎵 bioacoustics, 🧠 deep learning, and large-scale ecological data analysis, with a focus on building practical tools that bridge the gap between research and real-world conservation applications.

I coordinate 🌍 TABMON, a Biodiversa+ funded project establishing a transnational acoustic biodiversity monitoring network spanning Norway, the Netherlands, France, and Spain. In this project we are using autonomous recorders and AI to study birds and generate reliable biodiversity indicators that directly support EU environmental policy and enhance traditional monitoring programs with unprecedented scale and precision.

I also lead a work package in 🔊 ROaR, an innovative collaboration with SINTEF and Norsonic where we develop methods that allow AI models to perform well with minimal labeled data. The main goal is to build scalable, cost-effective solutions that reduce dependency on expensive manual annotation.

Beyond these, I develop practical AI solutions for ecology:
🦅 Few-shot learning algorithms for detecting rare and endangered species,
📊 Scalable workflows for processing massive acoustic datasets in real-time,
🔒 Privacy-preserving techniques for handling human sounds in passive monitoring systems,
🤝 Applied conservation projects focused on human–wildlife coexistence, disturbance impact assessment, and citizen-science data quality enhancement.

My technical expertise spans 🐍 Python (machine learning, audio processing, data pipelines) and 📈 R (statistical modeling, data visualization, ecological analysis). I actively maintain and contribute to open-source repositories that serve both our internal research needs and the broader scientific community. 💻✨