Rossana Cunha

Papers

Total Citations

H-Index

About

Rossana Cunha is a pioneering researcher at the intersection of natural language generation and environmental journalism. Her key research areas include computational journalism, data-driven storytelling, and applied natural language processing for social impact. Cunha’s most notable contribution is the development of **DaMata**, a robot-journalist system that autonomously covers deforestation in the Brazilian Amazon. Introduced in her 2020 demo paper, DaMata leverages a pipeline architecture of Natural Language Generation to transform raw public data from DETER—Brazil’s real-time deforestation monitoring system—into multilingual daily and monthly reports. This work represents a significant advance in automated journalism, demonstrating how AI can democratize access to critical environmental information and hold authorities accountable. While her citation count (2) reflects the niche, emerging nature of this field, the real-world impact of DaMata is substantial: it has been deployed to produce accessible, timely reports for journalists, policymakers, and the public, bridging the gap between complex satellite data and actionable news. Cunha’s work exemplifies how computational methods can serve pressing societal needs, making her a notable figure in the growing domain of AI for social good.