Ben McEwen

Kia ora! I am a postdoctoral researcher specialising in audio machine learning and bioacoustics based at Tilburg University, Netherlands. My research interests include active learning and uncertainty quantification for scaleable and data-efficient biodiversity monitoring.

My current project is TABMON where I am contributing to the development of a transnational biodiversity monitoring system with autonomous acoustic sensors from Norway to Spain.

I am the co-lead of the Listening Lab a multidisciplinary research group developing computational bioacoustic tools for conservation in New Zealand. I completed my PhD in computer Science from the Unversity of Canterbury where I developed methods for detection of invasive species. I am especially interested in how computational tools can aid in the detection of rare, at-risk and invasive species.

News

Oct 29, 2025	Co-organising the BioDCASE Workshop — See you at the upcoming BioDCASE and DCASE Workshop!
Sep 07, 2025	IBAC Conference — I presented our research related to Active Sampling for Data Efficient Large-Scale Bioacoustic Monitoring at the International Bioacoustics Congress in Denmark. Check out the poster here.
Oct 01, 2024	Starting Postdoctoral Research in the Netherlands — I’ve joined Tilburg University as a postdoctoral researcher in Dr. Dan Stowell’s group, working on the transnational TABMON biodiversity monitoring project. Learn more here.
Aug 01, 2024	PhD Completed — I’ve completed my PhD Computational Bioacoustics for the Detection of Rare Acoustic Events. You can read the full thesis here.

Latest Posts

Sep 05, 2025	Data Efficient Large-Scale Bioacoustic Monitoring Developing a transnational biodiversity monitoring network and data pipeline.
Mar 15, 2025	Stratified Active Learning Improving model generalisation across diverse ecosystems and changing soundscapes.

Selected Publications

Check out my other papers on Google Scholar

Pre-Print

Data-driven Sampling Strategies for Fine-Tuning Bird Detection Models

Corentin Bernard, Ben McEwen, Benjamin Cretois, and 3 more authors

bioRxiv, 2025

Bib HTML

@article{bernard2025data,
  title = {Data-driven Sampling Strategies for Fine-Tuning Bird Detection Models},
  author = {Bernard, Corentin and McEwen, Ben and Cretois, Benjamin and Glotin, Herve and Stowell, Dan and Marxer, Ricard},
  journal = {bioRxiv},
  pages = {2025--10},
  year = {2025},
  publisher = {Cold Spring Harbor Laboratory},
}

Pre-Print

Stratified Active Learning for Spatiotemporal Generalisation in Large-Scale Bioacoustic Monitoring

Ben McEwen, Corentin Bernard, and Dan Stowell

bioRxiv, 2025

Bib HTML

@article{mcewen2025stratified,
  title = {Stratified Active Learning for Spatiotemporal Generalisation in Large-Scale Bioacoustic Monitoring},
  author = {McEwen, Ben and Bernard, Corentin and Stowell, Dan},
  journal = {bioRxiv},
  pages = {2025--09},
  year = {2025},
  publisher = {Cold Spring Harbor Laboratory},
}

Thesis

Computational Bioacoustics for the Detection of Rare Acoustic Events

Ben McEwen

2024

Bib HTML

Journal Paper

Active Few-Shot Learning for Rare Bioacoustic Feature Annotation

Ben McEwen

Journal of Ecological Informatics, 2024

Bib HTML

@article{mcewen2024active,
  title = {Active Few-Shot Learning for Rare Bioacoustic Feature Annotation},
  author = {McEwen, Ben},
  year = {2024},
  journal = {Journal of Ecological Informatics},
}