Juan Sebastián Cañas


¡Hola! I'm an applied mathematician passionate about artificial intelligence for social impact and sustainability. My long-term goal is to learn, understand, and construct computational models to solve real-world problems in socio-ecological systems, biodiversity conservation, and climate change.

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I’m a researcher at the Humboldt Institute in Colombia and a collaborating researcher at the Mila-Quebec AI Institute. I work on machine learning for ecological problems, living between Audiomoths and Moths. Specifically, I work on ecoacoustics and bioacoustics in different groups such as amphibians, bats, birds, insects, and the soundscape. Recently, I started to work on computer vision for automated monitoring of insects. Previously, I was an undergraduate student at the National University of Colombia in the Mathematics Department working with Prof. Francisco Gómez where I worked on interpretability in healthcare and diverse problems in policy.

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Journal Publications


Research Interest

Ecology and biodiversity monitoring have a symbiotic relationship with machine learning. On one hand, machine learning offers a set of novel methods to process, extract, and analyze ecological data. On the other hand, ecology could be seen as a playground for exploring the scientific foundations of machine learning. Ecological systems are unique in scale, complexity, and richness. These problems often involve multiple parties for combinatorial decisions in highly dynamic and uncertain environments. Hence, machine learning challenges arise such as domain shift, spatiotemporal correlations, fine-grained categories, learning across data modalities, self-supervised representation learning, human-machine collaboration, and long-tailed distributions. Finally, I’m also interested in how to work together with local communities to co-create conservation tools that have an impact on biodiversity conservation.

Media (in Spanish)



jcanas (at) humboldt.org.co