Laura Pereda
Papers
1
Total Citations
3
H-Index
1
About
Laura Pereda is a marine robotics and environmental monitoring researcher whose work bridges autonomous systems, computer vision, and marine ecology. Her primary research focuses on developing novel methods for underwater environmental assessment, particularly using autonomous marine robots equipped with deep learning algorithms to monitor and measure seagrass ecosystems. Her most cited paper, "Measuring the temporal evolution of seagrass Posidonia oceanica coverage using autonomous marine robots and Deep Learning" (2024), introduces an innovative approach that combines robotic platforms with convolutional neural networks to track the health and coverage of the critical Mediterranean seagrass species *Posidonia oceanica* over time. This work addresses a pressing need for scalable, non-invasive monitoring of fragile marine habitats, offering a cost-effective alternative to traditional diver-based surveys. Though early in her career, her research has already garnered attention for its interdisciplinary impact, demonstrating how robotics and AI can directly support conservation efforts. Pereda’s contributions are particularly notable for their potential to automate large-scale ecological monitoring, providing real-time data that can inform policy and management of coastal ecosystems. Her work exemplifies the growing synergy between engineering and environmental science, positioning her as a rising voice in the field of autonomous marine observation.
Research Focus
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Top Papers
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