Editorial illustration of an academic cap and a network of knowledge nodes, in the colors of the Costa Rican flag.

Erick Mata-Montero

Erick Mata-Montero brings together two things that in Costa Rica should always go together: artificial intelligence and biodiversity. He is a professor and researcher in the School of Computer Engineering at the Costa Rica Institute of Technology (TEC), specializing in biodiversity informatics.

Key facts

Why he is a leader

Costa Rica is home to about 5% of the world’s known biodiversity. Adding artificial intelligence to that wealth is not a technical whim: it is a way to care for it better. That is Mata-Montero’s territory.

He is co-author of research that used deep learning to identify native Costa Rican tree species from images of wood cuts, published in the scientific journal Frontiers in Plant Science. The team built its own dataset with more than a hundred native species and trained neural networks to recognize them. It is a clear example of AI with a sense of place: frontier technology put to work on a deeply Costa Rican problem.

His career also connects him with conservation: he directed the Biodiversity Informatics Program at the National Biodiversity Institute (INBio), a historic bridge between computing and the study of nature in the country.

His contribution to the ecosystem

Mata-Montero shows that Costa Rican artificial intelligence does not have to copy the agendas of large countries. It can start from what the country has that is unique, its nature, and turn that advantage into original, internationally recognized research.

Frequently asked questions

Who is Erick Mata-Montero?
He is a professor and researcher in the School of Computer Engineering at the Costa Rica Institute of Technology, specializing in biodiversity informatics and deep learning applied to species identification. He holds a doctorate from the University of Oregon, United States.
How is artificial intelligence applied to biodiversity?
Through computer vision and deep learning, plant and animal species can be identified from images. Mata-Montero and his team trained neural networks to recognize native Costa Rican tree species from images of wood cuts.

Sources

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