Tilburg University department Cognitive Science and Artificial Intelligence

AI for Nature and Environment

The biodiversity crisis and climate crisis call for enormous ambition. They will require huge changes in society, such as land-use management. In order to monitor the natural world, and manage our relationship with it, we need rapid high-precision information and predictive modelling - AI can help to take the pulse of nature.

  • Dan Stowell

    dr. Dan Stowell

    Principal Investigator

We develop AI methods for monitoring wildlife and our environment:

  • AI for animal sound recognition
    • Develop AI methodology across a wide range of acoustic monitoring scenarios, for all our important species
    • High-precision AI even for small-data bioacoustics issues (e.g., rare species, individuals)
    • Animal vocal interaction - not only detecting animal calls, but also their patterns of interaction, and how these are affected by context
  • Europe-wide AI nature monitoring (with Arise, and Horizon Europe funded projects)
    • Ensure AI outputs can be integrated with later analysis e.g., statistical ecology
  • Investigate AI for reducing carbon emissions (e.g., predictive monitoring in electricity generation)
  • Implement environmentally responsible AI (e.g., low power/low CO2 emissions)
  • Develop solutions that are widely applicable, e.g., useful in low-resource and poorer countries

Methods include deep learning, nonparametric Bayesian estimation (Gaussian processes), and other statistical machine learning methods, combined with acoustic signal processing techniques.


  • Arise programme: Dutch nation-wide sound and image nature monitoring
  • Horizon Europe funded projects (MAMBO, GUARDEN): Europe-wide sound and image nature monitoring
  • Few-shot bioacoustic sound event detection
  • Biodiversity monitoring in urban/construction sites (with Heijmans and others)
  • Vocal interactions


This research line is developed as a close and ongoing collaboration with:

  • Naturalis Biodiversity Centre
  • Jheronimus Academy of Data Science