A collection of my research projects in AI, bioacoustics, and biodiversity conservation. All the code I produce is hoted on our institutional GitHub NINAnor

🤝 Collaboration

I'm always open to new collaborations and research opportunities. If you're interested in working together on AI for conservation or bioacoustic analysis, please don't hesitate to reach out!

Get in Touch

🚀 Present Projects

Biodiversity monitoring

TABMON

Deployment of acoustic recorders across Europe to study bird diversity

Machine learning

ROaR

Creating models that can generalise to other classes with not much annotations

Restoration

ForPEAT

Sustainable Forest Practices and Nature Restoration on Peat Soils, using bioacoustics as a way of monitoring recovery

Fish conservation

FishPath

Using turbulent eddies to create paths for safe downstream migration for salmonids and eels past hydropower intakes

Application

TABMON Dashboard

An Streamlit application designed to visualize the TABMON dataset

📚 Past Projects

Machine Learning

DCASE 2023 Challenge

Few-shot bioacoustic event detection system for rare species monitoring using advanced deep learning techniques.

Machine Learning

ecoVAD

A deep learning-powered voice activity detection algorithm specifically designed for ecological soundscape analysis.

Machine Learning

Snowmobile detector

A model to detect whether snowmobiles are present in near-real time

Application

BEATs trainer

A high level API for training BEATs, a powerful deep-learning acoustic classifier

Application

CarbonViewer

An R Shiny application designed to calculate and visualize carbon storage in peatland areas.